Benchmarks vs. its predecessor (Gemini 3.6 Flash)

The largest gains are in complex software engineering and document understanding. On DeepSWE V1.1, 3.7 Flash's 65% gets close to GPT-5.6 Terra's performance in that specific evaluation .

However, Google's own competitors still lead on widely-cited coding benchmarks. For context: Claude Sonnet 5 scored 76.1% on Terminal-Bench 2.1 and 63.2% on SWE-Bench Pro, and GPT-5.6 Terra scored roughly 70% and 60%, respectively .

Pricing: 50% cheaper than Gemini 3.6 Flash

Gemini 3.7 Flash launched at an introductory price of $0.75 per million input tokens and $3.75 per million output tokens — 50% cheaper than Gemini 3.6 Flash, which was priced at $1.50/$7.50 . This introductory rate runs through December 31, 2026, after which it reverts to $1.50/$7.50 .

Comparative pricing (per million tokens, input/output):

3.7 Flash undercuts both Claude Sonnet 5 and GPT-5.6 Terra by roughly 60–75% on a blended cost basis . But on raw coding benchmarks, the competitors still lead. For developers, 3.7 Flash offers a strong cost-to-performance ratio for high-volume agentic tasks where absolute top-tier accuracy is not required.

Status of the delayed flagship Gemini 3.5 Pro

• May 2026: Announced at Google I/O with a promised June release window . That deadline passed without a release.
• July 2026: Bloomberg reported the model is "months behind schedule" because its coding performance fell short of internal goals . Alphabet's market cap dropped roughly $200 billion (4.4%) on the news .
• As of August 13, 2026: Google still provided no release date or timeline for Gemini 3.5 Pro . The company only says the model is "being tested with partners and coming soon" . It has no entry in the Gemini API and no official spec sheet .

Leadership changes and strategic pressures at Google DeepMind

On August 5, 2026, Alphabet announced a sweeping AI leadership restructuring :

• Demis Hassabis stepped down as Google DeepMind CEO to become chairman of the unit and chief scientist at Alphabet . The move formalized a shift away from day-to-day management toward AGI strategy and scientific research . Tension between Hassabis's long-term scientific ambitions and Google's need to commercialize AI quickly was cited as a factor .
• Jeff Dean (Google's longtime AI leader) and other key engineers left to found a new startup . Two star researchers had departed to AI rivals in June .
• Google is consolidating AI efforts in its California headquarters, weakening the UK-based DeepMind operation .
• Fortune reported the shakeup was driven by low morale, a talent exodus, and model delays — with stalled models, missed deadlines, and staff burnout cited as key contributors . Experts described it as the biggest restructuring since Google Brain merged into DeepMind .

Hassabis was replaced in daily operations by Koray Kavukcuoglu, DeepMind's chief technology officer, who is now senior vice president reporting directly to Sundar Pichai .

Benchmarks vs. its predecessor (Gemini 3.6 Flash)

The largest gains are in complex software engineering and document understanding. On DeepSWE V1.1, 3.7 Flash's 65% gets close to GPT-5.6 Terra's performance in that specific evaluation .

However, Google's own competitors still lead on widely-cited coding benchmarks. For context: Claude Sonnet 5 scored 76.1% on Terminal-Bench 2.1 and 63.2% on SWE-Bench Pro, and GPT-5.6 Terra scored roughly 70% and 60%, respectively .

Pricing: 50% cheaper than Gemini 3.6 Flash

Gemini 3.7 Flash launched at an introductory price of $0.75 per million input tokens and $3.75 per million output tokens — 50% cheaper than Gemini 3.6 Flash, which was priced at $1.50/$7.50 . This introductory rate runs through December 31, 2026, after which it reverts to $1.50/$7.50 .

Comparative pricing (per million tokens, input/output):

3.7 Flash undercuts both Claude Sonnet 5 and GPT-5.6 Terra by roughly 60–75% on a blended cost basis . But on raw coding benchmarks, the competitors still lead. For developers, 3.7 Flash offers a strong cost-to-performance ratio for high-volume agentic tasks where absolute top-tier accuracy is not required.

Status of the delayed flagship Gemini 3.5 Pro

• May 2026: Announced at Google I/O with a promised June release window . That deadline passed without a release.
• July 2026: Bloomberg reported the model is "months behind schedule" because its coding performance fell short of internal goals . Alphabet's market cap dropped roughly $200 billion (4.4%) on the news .
• As of August 13, 2026: Google still provided no release date or timeline for Gemini 3.5 Pro . The company only says the model is "being tested with partners and coming soon" . It has no entry in the Gemini API and no official spec sheet .

Leadership changes and strategic pressures at Google DeepMind

On August 5, 2026, Alphabet announced a sweeping AI leadership restructuring :

• Demis Hassabis stepped down as Google DeepMind CEO to become chairman of the unit and chief scientist at Alphabet . The move formalized a shift away from day-to-day management toward AGI strategy and scientific research . Tension between Hassabis's long-term scientific ambitions and Google's need to commercialize AI quickly was cited as a factor .
• Jeff Dean (Google's longtime AI leader) and other key engineers left to found a new startup . Two star researchers had departed to AI rivals in June .
• Google is consolidating AI efforts in its California headquarters, weakening the UK-based DeepMind operation .
• Fortune reported the shakeup was driven by low morale, a talent exodus, and model delays — with stalled models, missed deadlines, and staff burnout cited as key contributors . Experts described it as the biggest restructuring since Google Brain merged into DeepMind .

Hassabis was replaced in daily operations by Koray Kavukcuoglu, DeepMind's chief technology officer, who is now senior vice president reporting directly to Sundar Pichai .