Research and fact-check: How powerful is Claude Opus 4.7?
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long horizon agentic wor...
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long horizon agentic work, long context tasks, and vision heavy workflows.[5][11] The important caveat is that Anthropic also s
Key takeaways
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact-checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long-horizon agentic work, long-context tasks, and vision-heavy workflows.[5][11] The important caveat is t
Anthropic’s own docs describe Opus 4.7 as its most capable generally available model, a position echoed by AWS’s Bedrock model card.
Opus 4.7 supports a 1 million token context window, 128k max output tokens, adaptive thinking, and reasoning support, placing it in the top tier for long-context and agentic use cases.
Anthropic reports a 13% coding performance improvement over Opus 4.6 on a 93-task benchmark, including solving tasks that previous models could not.
External benchmarks rank Opus 4.7 highly for coding and agentic execution but show it is not universally dominant across all benchmark families.
Claude Opus 4.7 is frontier-grade and clearly very strong, especially for coding, long-running agents, and large-context work. It is Anthropic’s most capable generally available model but not the best at every task, with Mythos Preview being broader and stronger overall.
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact-checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long-horizon agentic work, long-context tasks, and vision-heavy workflows.[5][11] The i
Key findings
Research answer
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact-checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long-horizon agentic work, long-context tasks, and vision-heavy workflows.[5][11] The important caveat is that Anthropic also says Claude Mythos Preview is more broadly capable, so “most powerful Claude overall” would be too strong.[11]
Key findings
Anthropic’s own docs describe Opus 4.7 as its “most capable generally available model,” and AWS’s Bedrock model card repeats that positioning.[5][2]
On specs, Opus 4.7 supports a 1M-token context window, 128k max output tokens, adaptive thinking, and reasoning support, which puts it in the top tier for long-context and agentic use cases.[5][2]
Anthropic says Opus 4.7 is a “notable improvement” over Opus 4.6 in advanced software engineering and complex long-running tasks.[11] Anthropic’s launch materials also highlight better instruction-following, self-verification, and greater consistency on hard coding work.[11]
Vision appears meaningfully upgraded. Anthropic says Opus 4.7 is its first model with high-resolution image support, raising maximum image resolution to 2576px / 3.75MP from 1568px / 1.15MP, with better low-level perception and image localization.[5]
The strongest concrete coding uplift I found in Anthropic’s public materials is a customer-reported result on Anthropic’s launch page: a 13% improvement over Opus 4.6 on a 93-task coding benchmark, including four tasks that Opus 4.6 and Sonnet 4.6 did not solve.[11]
External benchmark evidence is broadly positive but more mixed than the marketing language. On Vals AI’s model page, Opus 4.7 is ranked 1/40 on Vals Index, 1/41 on SWE-bench, 1/52 on Terminal-Bench 2.0, and 1/26 on Vibe Code Bench, which supports the claim that it is elite for coding and agentic execution.[12]
That same Vals page also shows Opus 4.7 is not first everywhere: it is ranked 7/96 on AIME, 13/103 on LiveCodeBench, and 7/66 on MMMU Pro, which suggests it is strongest in practical coding/agent workflows rather than universally dominant across every benchmark family.[12]
Anthropic explicitly says Opus 4.7 is “less broadly capable” than Mythos Preview.[11] So the cleanest summary is: top-tier and probably one of the best generally available models for coding agents, but not proven to be the best model at every task.[11][12]
Evidence notes
Main sources reviewed for this answer were Anthropic’s launch announcement, Anthropic’s model docs, Anthropic’s product page, AWS’s Bedrock model card, and Vals AI’s model page.[2][5][7][11][12]
The 13% coding-uplift figure comes from material on Anthropic’s launch page, not from a public benchmark report I independently verified in this pass.[11]
Vals AI notes that benchmark runs can use different providers and parameters, so leaderboard comparisons should be treated as informative but not perfectly apples-to-apples.[12]
Limitations / uncertainty
Most of the strongest public claims here are vendor-provided or partner-reported, which makes them useful but not as strong as a broad independent audit.[5][11]
I did not find enough public evidence in this pass to claim Opus 4.7 is unambiguously “the best model overall.”[11][12]
Summary
A careful fact-checked answer is: Claude Opus 4.7 is frontier-grade and clearly very strong, especially for coding, long-running agents, and large-context work.[5][11][12] The evidence supports “Anthropic’s most capable generally available model,” but not “best at everything,” and Anthropic itself says Mythos Preview is broader and stronger overall.[11]
If you want, I can next do one of two useful follow-ups: a direct comparison of Opus 4.7 vs GPT-5.4/Gemini 3.1 Pro, or a “should I use it?” breakdown by coding, research, writing, and cost.
Supporting visuals
Anthropic releases Claude Opus 4.7: How to try itA smartphone screen displays the name "Claude" alongside a stylized sunburst or starburst icon, with a background featuring similar starburst patterns in white on an orange backdrop.ogdev products previewIntroducing Claude Opus 4.7 \ AnthropicA graphic illustration featuring a stylized silhouette of a human head with neural network connections on the left and a playful abstract drawing of a face with question marks on the right, referencing the Anthropic Claude Opus 4.7 announcement.Introducing Claude Opus 4.7 \ AnthropicA comparative table displaying performance metrics of different AI models, highlighting the advancements of Anthropic's Claude Opus 4.7 over previous versions and competitors, with specific emphasis on its high score of 93.9% in Agentic coding.Introducing Claude Opus 4.7 \ AnthropicA line chart compares the performance of Claude Opus 4.7 and 4.6 in internal autonomous agentic coding evaluation, showing scores increasing with effort level.Introducing Claude Opus 4.7 \ AnthropicA bar chart comparing Elo scores of different AI models, with "Opus 4.7" having the highest score.2VmpYF 1AW7o8bj00Anthropic logoUSimage
Research conversation
You
Research question
Research and fact-check: How powerful is Claude Opus 4.7?
Studio Global AI12 sources
Cited answer
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact-checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long-horizon agentic work, long-context tasks, and vision-heavy workflows.[5][11] The important caveat is that Anthropic also says Claude Mythos Preview is more broadly capable, so “most powerful Claude overall” would be too strong.[11]
Key findings
Anthropic’s own docs describe Opus 4.7 as its “most capable generally available model,” and AWS’s Bedrock model card repeats that positioning.[5][2]
On specs, Opus 4.7 supports a 1M-token context window, 128k max output tokens, adaptive thinking, and reasoning support, which puts it in the top tier for long-context and agentic use cases.[5][2]
Anthropic says Opus 4.7 is a “notable improvement” over Opus 4.6 in advanced software engineering and complex long-running tasks.[11] Anthropic’s launch materials also highlight better instruction-following, self-verification, and greater consistency on hard coding work.[11]
Vision appears meaningfully upgraded. Anthropic says Opus 4.7 is its first model with high-resolution image support, raising maximum image resolution to 2576px / 3.75MP from 1568px / 1.15MP, with better low-level perception and image localization.[5]
The strongest concrete coding uplift I found in Anthropic’s public materials is a customer-reported result on Anthropic’s launch page: a 13% improvement over Opus 4.6 on a 93-task coding benchmark, including four tasks that Opus 4.6 and Sonnet 4.6 did not solve.[11]
External benchmark evidence is broadly positive but more mixed than the marketing language. On Vals AI’s model page, Opus 4.7 is ranked 1/40 on Vals Index, 1/41 on SWE-bench, 1/52 on Terminal-Bench 2.0, and 1/26 on Vibe Code Bench, which supports the claim that it is elite for coding and agentic execution.[12]
That same Vals page also shows Opus 4.7 is not first everywhere: it is ranked 7/96 on AIME, 13/103 on LiveCodeBench, and 7/66 on MMMU Pro, which suggests it is strongest in practical coding/agent workflows rather than universally dominant across every benchmark family.[12]
Anthropic explicitly says Opus 4.7 is “less broadly capable” than Mythos Preview.[11] So the cleanest summary is: top-tier and probably one of the best generally available models for coding agents, but not proven to be the best model at every task.[11][12]
Evidence notes
Main sources reviewed for this answer were Anthropic’s launch announcement, Anthropic’s model docs, Anthropic’s product page, AWS’s Bedrock model card, and Vals AI’s model page.[2][5][7][11][12]
The 13% coding-uplift figure comes from material on Anthropic’s launch page, not from a public benchmark report I independently verified in this pass.[11]
Vals AI notes that benchmark runs can use different providers and parameters, so leaderboard comparisons should be treated as informative but not perfectly apples-to-apples.[12]
Limitations / uncertainty
Most of the strongest public claims here are vendor-provided or partner-reported, which makes them useful but not as strong as a broad independent audit.[5][11]
I did not find enough public evidence in this pass to claim Opus 4.7 is unambiguously “the best model overall.”[11][12]
Summary
A careful fact-checked answer is: Claude Opus 4.7 is frontier-grade and clearly very strong, especially for coding, long-running agents, and large-context work.[5][11][12] The evidence supports “Anthropic’s most capable generally available model,” but not “best at everything,” and Anthropic itself says Mythos Preview is broader and stronger overall.[11]
If you want, I can next do one of two useful follow-ups: a direct comparison of Opus 4.7 vs GPT-5.4/Gemini 3.1 Pro, or a “should I use it?” breakdown by coding, research, writing, and cost.
People also ask
What is the short answer to "Research and fact-check: How powerful is Claude Opus 4.7?"?
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact-checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long-horizon agentic work, long-context tasks, and vision-heavy workflows.[5][11] The important caveat is t
What are the key points to validate first?
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact-checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long-horizon agentic work, long-context tasks, and vision-heavy workflows.[5][11] The important caveat is t Anthropic’s own docs describe Opus 4.7 as its most capable generally available model, a position echoed by AWS’s Bedrock model card.
What should I do next in practice?
Opus 4.7 supports a 1 million token context window, 128k max output tokens, adaptive thinking, and reasoning support, placing it in the top tier for long-context and agentic use cases.
Which related topic should I explore next?
Continue with "Research and fact-check: GPT-5.5 Spud, Agentic coding and tool orchestration, including tool calling, web search, and tool-heavy workflows." for another angle and extra citations.
Cross-check this answer against "Research and fact-check: GPT-5.5 Spud, Long-context reliability and instruction retention across extended workflows.".
Claude Opus 4.5 Launch: #1 in Coding, 1/3 the Price. Anthropic’s new flagship Claude Opus 4.7 is here — +13% on a 93-task coding benchmark, 3× production tasks on Rakuten-SWE-Bench, new xhigh effort level, ultrareview in Claude Code. from openai import OpenAI from openai import OpenAI client = OpenAI(client = OpenAI( api_key="your-apiyi-key", api_key ="your-apiyi-key", base_url="https://api.apiyi.com/v1" base_url ="https://api.apiyi.com/v1")) response = client.chat.completions.create(response = client.chat.completions.create( model="claude-opus-4-7", model ="claude-opus-4-7", messages=[ mes…
Claude Opus 4.7 introduces task budgets. This new tokenizer may use roughly 1x to 1.35x as many tokens when processing text compared to previous models (up to ~35% more, varying by content), and i.j4i.i2
On April 16, Anthropic launched Claude Opus 4.7, a coding-focused upgrade over Opus 4.6 that gives developers a 1M-token context window while tightening several API behaviors. That is the central product move in the launch: Anthropic is trying to make the public Opus line look credible for sustained technical work without moving customers into a separate long-context tier. Anthropic keeps using the public Opus line for iterative, production-facing gains in technical work instead of presenting each release as a new strategic identity. Anthropic is commercializing the model it can document, pri…
Claude Opus 4.7 arrived as a major Anthropic release and immediately changed the practical conversation around Claude’s high-end model tier. Claude Sonnet remains the more broadly economical and often faster tier for many production tasks, while Opus is being framed as the model for more difficult workloads that benefit from deeper reasoning, stronger persistence across multi-step work, and more careful handling of complex inputs. · Claude Opus 4.7 is the highest-tier generally available Claude model in Anthropic’s public lineup.. | Claude Opus 4.7 | Current generally available flagship |…
Skip to main content. Sign In. . Anthropic's April 16 release reports the following benchmark shifts — all Anthropic-conducted unless otherwise noted:. * [Claude Managed Agents Pricing: What You Actually Pay](htt…
anthropic/claude-opus-4-7. Release Date: 4/16/2026. Some benchmarks may use different provider and parameters. Please refer to the benchmark page for more information. Vals IndexVals IndexVals Multimodal Index. ##### Contact us. Proprietary Benchmarks (contact us to get access).
ReportsPublic URLApr 19, 202612 sources
Research and fact-check: How powerful is Claude Opus 4.7?
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long horizon agentic wor...
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long horizon agentic work, long context tasks, and vision heavy workflows.[5][11] The important caveat is that Anthropic also s
Key takeaways
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact-checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long-horizon agentic work, long-context tasks, and vision-heavy workflows.[5][11] The important caveat is t
Anthropic’s own docs describe Opus 4.7 as its most capable generally available model, a position echoed by AWS’s Bedrock model card.
Opus 4.7 supports a 1 million token context window, 128k max output tokens, adaptive thinking, and reasoning support, placing it in the top tier for long-context and agentic use cases.
Anthropic reports a 13% coding performance improvement over Opus 4.6 on a 93-task benchmark, including solving tasks that previous models could not.
External benchmarks rank Opus 4.7 highly for coding and agentic execution but show it is not universally dominant across all benchmark families.
Claude Opus 4.7 is frontier-grade and clearly very strong, especially for coding, long-running agents, and large-context work. It is Anthropic’s most capable generally available model but not the best at every task, with Mythos Preview being broader and stronger overall.
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact-checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long-horizon agentic work, long-context tasks, and vision-heavy workflows.[5][11] The i
Key findings
Research answer
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact-checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long-horizon agentic work, long-context tasks, and vision-heavy workflows.[5][11] The important caveat is that Anthropic also says Claude Mythos Preview is more broadly capable, so “most powerful Claude overall” would be too strong.[11]
Key findings
Anthropic’s own docs describe Opus 4.7 as its “most capable generally available model,” and AWS’s Bedrock model card repeats that positioning.[5][2]
On specs, Opus 4.7 supports a 1M-token context window, 128k max output tokens, adaptive thinking, and reasoning support, which puts it in the top tier for long-context and agentic use cases.[5][2]
Anthropic says Opus 4.7 is a “notable improvement” over Opus 4.6 in advanced software engineering and complex long-running tasks.[11] Anthropic’s launch materials also highlight better instruction-following, self-verification, and greater consistency on hard coding work.[11]
Vision appears meaningfully upgraded. Anthropic says Opus 4.7 is its first model with high-resolution image support, raising maximum image resolution to 2576px / 3.75MP from 1568px / 1.15MP, with better low-level perception and image localization.[5]
The strongest concrete coding uplift I found in Anthropic’s public materials is a customer-reported result on Anthropic’s launch page: a 13% improvement over Opus 4.6 on a 93-task coding benchmark, including four tasks that Opus 4.6 and Sonnet 4.6 did not solve.[11]
External benchmark evidence is broadly positive but more mixed than the marketing language. On Vals AI’s model page, Opus 4.7 is ranked 1/40 on Vals Index, 1/41 on SWE-bench, 1/52 on Terminal-Bench 2.0, and 1/26 on Vibe Code Bench, which supports the claim that it is elite for coding and agentic execution.[12]
That same Vals page also shows Opus 4.7 is not first everywhere: it is ranked 7/96 on AIME, 13/103 on LiveCodeBench, and 7/66 on MMMU Pro, which suggests it is strongest in practical coding/agent workflows rather than universally dominant across every benchmark family.[12]
Anthropic explicitly says Opus 4.7 is “less broadly capable” than Mythos Preview.[11] So the cleanest summary is: top-tier and probably one of the best generally available models for coding agents, but not proven to be the best model at every task.[11][12]
Evidence notes
Main sources reviewed for this answer were Anthropic’s launch announcement, Anthropic’s model docs, Anthropic’s product page, AWS’s Bedrock model card, and Vals AI’s model page.[2][5][7][11][12]
The 13% coding-uplift figure comes from material on Anthropic’s launch page, not from a public benchmark report I independently verified in this pass.[11]
Vals AI notes that benchmark runs can use different providers and parameters, so leaderboard comparisons should be treated as informative but not perfectly apples-to-apples.[12]
Limitations / uncertainty
Most of the strongest public claims here are vendor-provided or partner-reported, which makes them useful but not as strong as a broad independent audit.[5][11]
I did not find enough public evidence in this pass to claim Opus 4.7 is unambiguously “the best model overall.”[11][12]
Summary
A careful fact-checked answer is: Claude Opus 4.7 is frontier-grade and clearly very strong, especially for coding, long-running agents, and large-context work.[5][11][12] The evidence supports “Anthropic’s most capable generally available model,” but not “best at everything,” and Anthropic itself says Mythos Preview is broader and stronger overall.[11]
If you want, I can next do one of two useful follow-ups: a direct comparison of Opus 4.7 vs GPT-5.4/Gemini 3.1 Pro, or a “should I use it?” breakdown by coding, research, writing, and cost.
Supporting visuals
Anthropic releases Claude Opus 4.7: How to try itA smartphone screen displays the name "Claude" alongside a stylized sunburst or starburst icon, with a background featuring similar starburst patterns in white on an orange backdrop.ogdev products previewIntroducing Claude Opus 4.7 \ AnthropicA graphic illustration featuring a stylized silhouette of a human head with neural network connections on the left and a playful abstract drawing of a face with question marks on the right, referencing the Anthropic Claude Opus 4.7 announcement.Introducing Claude Opus 4.7 \ AnthropicA comparative table displaying performance metrics of different AI models, highlighting the advancements of Anthropic's Claude Opus 4.7 over previous versions and competitors, with specific emphasis on its high score of 93.9% in Agentic coding.Introducing Claude Opus 4.7 \ AnthropicA line chart compares the performance of Claude Opus 4.7 and 4.6 in internal autonomous agentic coding evaluation, showing scores increasing with effort level.Introducing Claude Opus 4.7 \ AnthropicA bar chart comparing Elo scores of different AI models, with "Opus 4.7" having the highest score.2VmpYF 1AW7o8bj00Anthropic logoUSimage
Research conversation
You
Research question
Research and fact-check: How powerful is Claude Opus 4.7?
Studio Global AI12 sources
Cited answer
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact-checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long-horizon agentic work, long-context tasks, and vision-heavy workflows.[5][11] The important caveat is that Anthropic also says Claude Mythos Preview is more broadly capable, so “most powerful Claude overall” would be too strong.[11]
Key findings
Anthropic’s own docs describe Opus 4.7 as its “most capable generally available model,” and AWS’s Bedrock model card repeats that positioning.[5][2]
On specs, Opus 4.7 supports a 1M-token context window, 128k max output tokens, adaptive thinking, and reasoning support, which puts it in the top tier for long-context and agentic use cases.[5][2]
Anthropic says Opus 4.7 is a “notable improvement” over Opus 4.6 in advanced software engineering and complex long-running tasks.[11] Anthropic’s launch materials also highlight better instruction-following, self-verification, and greater consistency on hard coding work.[11]
Vision appears meaningfully upgraded. Anthropic says Opus 4.7 is its first model with high-resolution image support, raising maximum image resolution to 2576px / 3.75MP from 1568px / 1.15MP, with better low-level perception and image localization.[5]
The strongest concrete coding uplift I found in Anthropic’s public materials is a customer-reported result on Anthropic’s launch page: a 13% improvement over Opus 4.6 on a 93-task coding benchmark, including four tasks that Opus 4.6 and Sonnet 4.6 did not solve.[11]
External benchmark evidence is broadly positive but more mixed than the marketing language. On Vals AI’s model page, Opus 4.7 is ranked 1/40 on Vals Index, 1/41 on SWE-bench, 1/52 on Terminal-Bench 2.0, and 1/26 on Vibe Code Bench, which supports the claim that it is elite for coding and agentic execution.[12]
That same Vals page also shows Opus 4.7 is not first everywhere: it is ranked 7/96 on AIME, 13/103 on LiveCodeBench, and 7/66 on MMMU Pro, which suggests it is strongest in practical coding/agent workflows rather than universally dominant across every benchmark family.[12]
Anthropic explicitly says Opus 4.7 is “less broadly capable” than Mythos Preview.[11] So the cleanest summary is: top-tier and probably one of the best generally available models for coding agents, but not proven to be the best model at every task.[11][12]
Evidence notes
Main sources reviewed for this answer were Anthropic’s launch announcement, Anthropic’s model docs, Anthropic’s product page, AWS’s Bedrock model card, and Vals AI’s model page.[2][5][7][11][12]
The 13% coding-uplift figure comes from material on Anthropic’s launch page, not from a public benchmark report I independently verified in this pass.[11]
Vals AI notes that benchmark runs can use different providers and parameters, so leaderboard comparisons should be treated as informative but not perfectly apples-to-apples.[12]
Limitations / uncertainty
Most of the strongest public claims here are vendor-provided or partner-reported, which makes them useful but not as strong as a broad independent audit.[5][11]
I did not find enough public evidence in this pass to claim Opus 4.7 is unambiguously “the best model overall.”[11][12]
Summary
A careful fact-checked answer is: Claude Opus 4.7 is frontier-grade and clearly very strong, especially for coding, long-running agents, and large-context work.[5][11][12] The evidence supports “Anthropic’s most capable generally available model,” but not “best at everything,” and Anthropic itself says Mythos Preview is broader and stronger overall.[11]
If you want, I can next do one of two useful follow-ups: a direct comparison of Opus 4.7 vs GPT-5.4/Gemini 3.1 Pro, or a “should I use it?” breakdown by coding, research, writing, and cost.
People also ask
What is the short answer to "Research and fact-check: How powerful is Claude Opus 4.7?"?
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact-checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long-horizon agentic work, long-context tasks, and vision-heavy workflows.[5][11] The important caveat is t
What are the key points to validate first?
Claude Opus 4.7 looks very powerful by current public evidence: the safest fact-checked claim is that it is Anthropic’s strongest generally available model, with particular strength in coding, long-horizon agentic work, long-context tasks, and vision-heavy workflows.[5][11] The important caveat is t Anthropic’s own docs describe Opus 4.7 as its most capable generally available model, a position echoed by AWS’s Bedrock model card.
What should I do next in practice?
Opus 4.7 supports a 1 million token context window, 128k max output tokens, adaptive thinking, and reasoning support, placing it in the top tier for long-context and agentic use cases.
Which related topic should I explore next?
Continue with "Research and fact-check: GPT-5.5 Spud, Agentic coding and tool orchestration, including tool calling, web search, and tool-heavy workflows." for another angle and extra citations.
Cross-check this answer against "Research and fact-check: GPT-5.5 Spud, Long-context reliability and instruction retention across extended workflows.".
Claude Opus 4.5 Launch: #1 in Coding, 1/3 the Price. Anthropic’s new flagship Claude Opus 4.7 is here — +13% on a 93-task coding benchmark, 3× production tasks on Rakuten-SWE-Bench, new xhigh effort level, ultrareview in Claude Code. from openai import OpenAI from openai import OpenAI client = OpenAI(client = OpenAI( api_key="your-apiyi-key", api_key ="your-apiyi-key", base_url="https://api.apiyi.com/v1" base_url ="https://api.apiyi.com/v1")) response = client.chat.completions.create(response = client.chat.completions.create( model="claude-opus-4-7", model ="claude-opus-4-7", messages=[ mes…
Claude Opus 4.7 introduces task budgets. This new tokenizer may use roughly 1x to 1.35x as many tokens when processing text compared to previous models (up to ~35% more, varying by content), and i.j4i.i2
On April 16, Anthropic launched Claude Opus 4.7, a coding-focused upgrade over Opus 4.6 that gives developers a 1M-token context window while tightening several API behaviors. That is the central product move in the launch: Anthropic is trying to make the public Opus line look credible for sustained technical work without moving customers into a separate long-context tier. Anthropic keeps using the public Opus line for iterative, production-facing gains in technical work instead of presenting each release as a new strategic identity. Anthropic is commercializing the model it can document, pri…
Claude Opus 4.7 arrived as a major Anthropic release and immediately changed the practical conversation around Claude’s high-end model tier. Claude Sonnet remains the more broadly economical and often faster tier for many production tasks, while Opus is being framed as the model for more difficult workloads that benefit from deeper reasoning, stronger persistence across multi-step work, and more careful handling of complex inputs. · Claude Opus 4.7 is the highest-tier generally available Claude model in Anthropic’s public lineup.. | Claude Opus 4.7 | Current generally available flagship |…
Skip to main content. Sign In. . Anthropic's April 16 release reports the following benchmark shifts — all Anthropic-conducted unless otherwise noted:. * [Claude Managed Agents Pricing: What You Actually Pay](htt…
anthropic/claude-opus-4-7. Release Date: 4/16/2026. Some benchmarks may use different provider and parameters. Please refer to the benchmark page for more information. Vals IndexVals IndexVals Multimodal Index. ##### Contact us. Proprietary Benchmarks (contact us to get access).
. 
. Read more. Read more. Read more. [Rea…
. Anthropic's April 16 release reports the following benchmark shifts — all Anthropic-conducted unless otherwise noted:. * [Claude Managed Agents Pricing: What You Actually Pay](htt…
. 
. ![Image 8: logo](https://www-cdn.anthropic.com/images/4zrzovbb/websit…