Google model

Gemini 3.7 Flash API

google/gemini-3.7-flash is Google's current Flash id in the NextModel catalog: $1.50 per million input tokens, $7.50 per million output tokens, $0.15 per million cache hits, and a 1,000,000 token context window. One integration fact decides most adoption choices: the catalog lists this id on the gemini API surface only, not on the OpenAI-compatible chat completions endpoint, so OpenAI SDK code must move to the Gemini request shape or pick a different id. The row lists Thinking, Function Calling, and Vision as capabilities. Against google/gemini-3.5-flash at $1.50 / $9.00, the input rate is identical and the output rate is $1.50 per million cheaper. No first-party benchmark scores or latency band are published for this id.

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GooglePlatform curatedCatalog
ThinkingFunction CallingVision

Price deadline

Gemini Flash prices rise Jan 1, 2027

Per Google's published pricing page, Gemini Flash input prices double on Jan 1, 2027. The same workload runs an order of magnitude cheaper on DeepSeek and GLM. Source: Google pricing Full price breakdown

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Input price$1.50 / 1M tokens
Output price$7.50 / 1M tokens
Context length1M tokens
Max output8.2k tokens

What is Gemini 3.7 Flash API in NextModel?

google/gemini-3.7-flash is Google's current Flash id in the NextModel catalog: $1.50 per million input tokens, $7.50 per million output tokens, $0.15 per million cache hits, and a 1,000,000 token context window. One integration fact decides most adoption choices: the catalog lists this id on the gemini API surface only, not on the OpenAI-compatible chat completions endpoint, so OpenAI SDK code must move to the Gemini request shape or pick a different id. The row lists Thinking, Function Calling, and Vision as capabilities. Against google/gemini-3.5-flash at $1.50 / $9.00, the input rate is identical and the output rate is $1.50 per million cheaper. No first-party benchmark scores or latency band are published for this id.

Gemini 3.7 Flash via NextModel: 1M-token context; $1.50 / 1M tokens in / $7.50 / 1M tokens out per 1M tokens. Capabilities: streaming, tool, json.

Best use cases

  • Codebases that already speak the Gemini generateContent shape and want 3.7 Flash's listed Thinking, Function Calling, and Vision capabilities at $1.50 / $7.50.
  • Output-heavy Gemini work: the $7.50 output rate undercuts gemini-3.5-flash's listed $9.00 while input stays $1.50.
  • Repeated-context jobs — long instructions or recurring document sets — that can earn the listed $0.15 per million cache-hit rate.

When not to use

  • OpenAI SDK chat completions code you will not adapt: this id is not served on that surface, and the mismatch surfaces at request time, not at signup.
  • Absolute cost-floor traffic: deepseek/deepseek-v4-flash lists $0.14 / $0.28 per million tokens, roughly a tenth of this id's rates on both axes.
  • Pipelines that require Streaming or Structured Outputs entries on the catalog row: this id lists Thinking, Function Calling, and Vision only.

OpenAI-compatible code example

request.sh
curl https://api.nextmodel.app/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $NEXTMODEL_API_KEY" \
  -d '{"model":"google/gemini-3.7-flash","messages":[{"role":"user","content":"Reply with OK."}]}'

Switching models only changes the model field.

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Compare Gemini 3.7 Flash

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Reading

Articles that explain Gemini 3.7 Flash

FAQ

Gemini 3.7 Flash API questions

What model id do I send for Gemini 3.7 Flash?

Send google/gemini-3.7-flash to the Gemini surface under https://api.nextmodel.app/v1/gemini. The catalog lists this id on the gemini API only — it is not available on the OpenAI-compatible chat completions endpoint, so OpenAI SDK calls need the Gemini request shape instead.

What does the catalog list for price and context?

$1.50 per million input tokens, $7.50 per million output tokens, and $0.15 per million cache hits. Context window: 1,000,000 tokens.

What should I treat as unverified?

Latency band and first-party benchmark scores are unpublished for this id. The Thinking, Function Calling, and Vision entries come from the catalog row, and the catalog publishes no quality scores behind them.

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