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Google: Gemini 3.7 Flash

High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning

Source-linked gemini-flash Closed weights Released 2026-08-13
API record Report
InputT
OutputT
Input price$0.75/M
Output price$3.75/M
Context1.04858M
Max output65.536K
Providers19
Inference availability

Providers

Provider-specific identifiers, limits, and listed prices per million tokens. Every row links back to the provider's own documentation.

Report a price
Providers offering Gemini 3.7 Flash
ProviderProvider model IDContextMax outputInputOutputCache readCapabilitiesDocs
OpenRouter google/gemini-3.7-flash 1.04858M 65.536K $0.375 $1.875 $0.037 ReasoningToolsJSON Docs ↗
NanoGPT google/gemini-3.7-flash 1.04858M 65.536K $0.375 $1.875 $0.037 ReasoningToolsJSON Docs ↗
Requesty gemini-3.7-flash 1.04858M 65.535K $0.75 $3.75 $0.075 ReasoningToolsJSON Docs ↗
Kilo Gateway google/gemini-3.7-flash 1.04858M 65.536K $0.75 $3.75 $0.075 ReasoningToolsJSON Docs ↗
Merge Gateway google/gemini-3.7-flash 1.04858M 65.536K $0.75 $3.75 $0.075 ReasoningToolsJSON Docs ↗
Vercel AI Gateway google/gemini-3.7-flash 1M 65.536K $0.75 $3.75 $0.075 ReasoningToolsJSON Docs ↗
LLM Gateway gemini-3.7-flash 1.04858M 65.536K $0.75 $3.75 $0.075 ReasoningToolsJSON Docs ↗
Google gemini-3.7-flash 1.04858M 65.536K $0.75 $3.75 $0.075 ReasoningToolsJSON Docs ↗
Vertex gemini-3.7-flash 1.04858M 65.536K $0.75 $3.75 $0.075 ReasoningToolsJSON Docs ↗
Eden AI vertex/gemini-3.7-flash 1.04858M 65.536K $0.75 $3.75 $0.075 ReasoningToolsJSON Docs ↗
CrossModel gemini/gemini-3.7-flash 1.04858M 65.536K $0.75 $3.75 $0.075 ReasoningToolsJSON Docs ↗
GitHub Copilot gemini-3.7-flash 1M 64K $0.75 $3.75 $0.075 ReasoningToolsJSON Docs ↗
Cortecs gemini-3.7-flash 1.04858M 1.04858M $0.75 $3.75 $0.075 ReasoningToolsJSON Docs ↗
Abacus gemini-3.7-flash 1.04858M 65.536K $0.75 $3.75 $0.075 ReasoningToolsJSON Docs ↗
AIHubMix gemini-3.7-flash 1.04858M 65.536K $0.75 $3.75 $0.075 ReasoningToolsJSON Docs ↗
Eden AI google/gemini-3.7-flash 1.04858M 65.536K $0.75 $3.75 $0.075 ReasoningToolsJSON Docs ↗
Eden AI vertex/gemini-flash-latest 1.04858M 65.536K $0.75 $3.75 $0.075 ReasoningToolsJSON Docs ↗
OpenCode Zen gemini-3.7-flash 1.04858M 65.536K $1.5 $7.5 $0.15 ReasoningToolsJSON Docs ↗
Venice AI gemini-3-7-flash 1M 65.536K $1.875 $9.375 $0.188 ReasoningToolsJSON Docs ↗

Capability badges appear only where the provider catalog explicitly lists support. A blank cell means the source is silent, not that the feature is absent.

Listed rates

Price across providers

Input price per million tokens as published by each provider. Bars are drawn from listed rates only — no traffic weighting, since the catalog observes no requests.

Lowest input $0.375/M

Across 19 priced providers

Median input $0.75/M

Midpoint of listed rates

Highest input $1.875/M

5.0× the lowest listed rate

Output range $1.875 – $9.375

Per million output tokens

OpenRouter $0.375/M
NanoGPT $0.375/M
Requesty $0.75/M
Kilo Gateway $0.75/M
Merge Gateway $0.75/M
Vercel AI Gateway $0.75/M
LLM Gateway $0.75/M
Google $0.75/M
Vertex $0.75/M
Eden AI $0.75/M
CrossModel $0.75/M
GitHub Copilot $0.75/M
Cortecs $0.75/M
Abacus $0.75/M
AIHubMix $0.75/M
Eden AI $0.75/M
Eden AI $0.75/M
OpenCode Zen $1.5/M
Venice AI $1.875/M
Cost calculator

Estimate a workload

$0.00
Excludes taxes, non-token charges, and tiered discounts.

2 providers list the identical $0.375 input rate, so price alone will not separate them — compare context limits, max output, and capabilities above.

Context limits also differ by provider, from 1M to 1.04858M tokens. Compare the provider table above before choosing on price alone.

Specification

Capabilities

Recorded from the source catalog and provider listings.

✓ Reasoning Yes
✓ Tool calling Yes
✓ Structured output Yes
✓ Attachments Yes
✓ Vision input Yes
× Open weights No
Creator
Google
Model family
gemini-flash
Knowledge cutoff
2026-03
License
Not documented
Release date
2026-08-13
Model ID
google/gemini-3.7-flash
Published evaluations

Benchmarks

Every result stays attached to its source, version, metric and harness. Scores from different versions are never merged, and the profile below plots each benchmark against its own population rather than on a shared scale.

Benchmark registry
Benchmark profile
Coding IndexCoding Index Agentic IndexAgentic Index Design Arena: w…Design Arena: website IntelligenceIntelligence Index Design Arena: c…Design Arena: codecategories Design Arena: g…Design Arena: gamedev Design Arena: d…Design Arena: dataviz Design Arena: u…Design Arena: uicomponent This model — Coding Index: 76.1 index (93.5th percentile) This model — Agentic Index: 45.1 index (82.1th percentile) This model — Design Arena: website: 1319 elo (95.8th percentile) This model — Intelligence Index: 56 index (89.6th percentile) This model — Design Arena: codecategories: 1334 elo (95.9th percentile) This model — Design Arena: gamedev: 1370 elo (95.9th percentile) This model — Design Arena: dataviz: 1317 elo (90.7th percentile) This model — Design Arena: uicomponent: 1317 elo (87.9th percentile)

Each axis is this model's percentile among the 8 benchmarks it has published results for, measured against every other model with a score on that same benchmark. Percentiles are used because benchmarks do not share a scale — a 60 on one is not a 60 on another. Hover any point for the raw score.

Coding Index index Source ↗
Coding Index #11 of 168
Agentic Index index Source ↗
Agentic Index #28 of 156
Design Arena: website elo Source ↗
Design Arena: website #5 of 154
Intelligence Index index Source ↗
Intelligence Index #16 of 154
Design Arena: codecategories elo Source ↗
Design Arena: codecategories #5 of 146
Design Arena: gamedev elo Source ↗
Design Arena: gamedev #6 of 146
Design Arena: dataviz elo Source ↗
Design Arena: dataviz #13 of 145
Design Arena: uicomponent elo Source ↗
Design Arena: uicomponent #17 of 141
Design Arena: 3d elo Source ↗
Design Arena: 3d #5 of 136
Design Arena: androidnative elo Source ↗
Design Arena: androidnative #7 of 54
DeepSWE — 1.1 resolve rate · 2026-08-13 Source ↗
DeepSWE #5 of 7
GDM-MRCR — v2 accuracy · 2026-08-13 Source ↗
GDM-MRCR #1 of 3
Terminal-Bench — 2.1 accuracy · 2026-08-13 Source ↗
85.8 2 models scored — too few for a distribution
AutomationBench accuracy · 2026-08-13 Source ↗
30.4 1 model scored — too few for a distribution
FrontierCode — 1.1 Main score · 2026-08-13 Source ↗
43.6 1 model scored — too few for a distribution
GDP.pdf accuracy · 2026-08-13 Source ↗
34.0 1 model scored — too few for a distribution

Each strip shows every published score for that benchmark, with this model marked. The lighter shape behind the ticks is the density of results, and the dashed line is the median.

Cost against capability

Price and performance

Listed input price plotted against Coding Index, the benchmark with the widest published coverage that this model appears in.

0 41 83 $0.01 $0.1 $1 $10 GPT-5.6 Luna — $0.2/M, score 71.4 GPT-5.6 Terra — $2/M, score 76.7 GPT-5.6 Sol — $5/M, score 77.4 SpaceXAI: Grok 4.5 — $2/M, score 72.4 Claude Sonnet 5 — $2/M, score 71.5 Z.ai: GLM 5.2 — $0.476/M, score 68.8 Kimi K2.7 Code — $0.95/M, score 60.8 Claude Fable 5 — $10/M, score 76.5 Nex AGI: Nex-N2-Pro — $0.25/M, score 59.1 Nemotron 3 Ultra 550B A55B — $0.5/M, score 49.3 Qwen: Qwen3.7 Plus — $0.32/M, score 55.9 MiniMax: MiniMax M3 — $0.3/M, score 58.6 Step 3.7 Flash — $0.185/M, score 39.6 Anthropic: Claude Opus 4.8 — $5/M, score 74.3 Qwen: Qwen3.7 Max — $1.475/M, score 66.0 SpaceXAI: Grok Build 0.1 — $1/M, score 51.5 Gemini 3.5 Flash — $1.5/M, score 70.1 inclusionAI: Ring-2.6-1T — $0.075/M, score 42.8 SpaceXAI: Grok 4.3 — $1.25/M, score 42.2 IBM: Granite 4.1 8B — $0.05/M, score 9.5 Mistral: Mistral Medium 3.5 — $1.5/M, score 46.9 Qwen: Qwen3.6 35B A3B — $0.14/M, score 41.9 Qwen: Qwen3.6 27B — $0.289/M, score 53.7 GPT-5.5 — $5/M, score 74.9 DeepSeek V4 Pro — $0.435/M, score 58.7 DeepSeek V4 Flash — $0.14/M, score 56.2 Hy3 preview — $0.066/M, score 58.8 MiMo-V2.5-Pro — $0.435/M, score 60.2 MiMo-V2.5 — $0.14/M, score 56.8 inclusionAI: Ling-2.6-flash — $0.01/M, score 25.3 Kimi K2.6 — $0.95/M, score 61.8 Anthropic: Claude Opus 4.7 — $5/M, score 73.6 Z.ai: GLM 5.1 — $0.966/M, score 55.8 Gemma 4 26B A4B IT — $0.06/M, score 39.3 Gemma 4 31B IT — $0.08/M, score 43.4 Qwen: Qwen3.6 Plus — $0.325/M, score 54.5 Trinity Large Thinking — $0.22/M, score 25.8 Kwaipilot: KAT-Coder-Pro V2 — $0.3/M, score 59.5 MiniMax: MiniMax M2.7 — $0.3/M, score 52.6 GPT-5.4 nano — $0.2/M, score 56.1 GPT-5.4 mini — $0.75/M, score 56.1 Mistral: Mistral Small 4 — $0.15/M, score 26.6 Nemotron 3 Super 120B A12B — $0.2/M, score 37.7 Qwen: Qwen3.5-9B — $0.1/M, score 28.7 GPT-5.4 — $2.5/M, score 71.1 Inception: Mercury 2 — $0.25/M, score 31.1 Gemini 3.1 Flash Lite Preview — $0.25/M, score 34.7 Qwen: Qwen3.5-35B-A3B — $0.225/M, score 37.0 Qwen: Qwen3.5-122B-A10B — $0.29/M, score 45.7 Gemini 3.1 Pro Preview — $2/M, score 68.8 Anthropic: Claude Sonnet 4.6 — $3/M, score 63.0 Qwen: Qwen3.5 397B A17B — $0.39/M, score 48.2 Qwen: Qwen3 Coder Next — $0.12/M, score 36.2 Kimi K2.5 — $0.6/M, score 46.8 Upstage: Solar Pro 3 — $0.15/M, score 16.2 Z.ai: GLM 4.7 — $0.4/M, score 45.3 Nemotron 3 Nano 30B A3B — $0.05/M, score 14.4 Mistral: Devstral 2 2512 — $0.4/M, score 31.3 Amazon: Nova 2 Lite — $0.3/M, score 23.0 Mistral: Ministral 3 14B 2512 — $0.2/M, score 14.4 Mistral: Ministral 3 8B 2512 — $0.15/M, score 9.7 Mistral: Ministral 3 3B 2512 — $0.1/M, score 4.8 Mistral: Mistral Large 3 2512 — $0.5/M, score 20.1 DeepSeek V3.2 — $0.18/M, score 44.2 GPT-5.1 — $1.25/M, score 49.4 Kimi K2 Thinking — $0.6/M, score 21.0 Anthropic: Claude Haiku 4.5 — $1/M, score 43.9 Z.ai: GLM 4.6 — $0.5/M, score 45.8 Anthropic: Claude Sonnet 4.5 — $3/M, score 52.1 DeepSeek: DeepSeek V3.1 Terminus — $0.27/M, score 43.5 Qwen: Qwen3 Next 80B A3B Thinking — $0.15/M, score 17.4 Qwen: Qwen3 30B A3B Thinking 2507 — $0.2/M, score 12.1 Mistral: Mistral Medium 3.1 — $0.4/M, score 20.5 GPT-5 — $1.25/M, score 37.8 GPT-5 Mini — $0.25/M, score 15.6 GPT OSS 120B — $0.03/M, score 30.4 GPT OSS 20B — $0.03/M, score 20.7 Qwen: Qwen3 235B A22B Thinking 2507 — $0.23/M, score 22.1 Gemini 2.5 Pro — $1.25/M, score 33.3 Anthropic: Claude Sonnet 4 — $3/M, score 37.6 Google: Gemma 3n 4B — $0.06/M, score 3.2 Qwen: Qwen3 8B — $0.117/M, score 9.0 Qwen: Qwen3 14B — $0.12/M, score 13.8 Qwen: Qwen3 32B — $0.08/M, score 15.3 GPT-4.1 mini — $0.4/M, score 20.2 GPT-4.1 nano — $0.1/M, score 11.1 Meta: Llama 4 Maverick — $0.2/M, score 16.3 Meta: Llama 4 Scout — $0.1/M, score 8.2 DeepSeek: DeepSeek V3 0324 — $0.27/M, score 21.2 Google: Gemma 3 4B — $0.05/M, score 2.7 Google: Gemma 3 12B — $0.05/M, score 5.8 Cohere: Command A — $2.5/M, score 27.8 Google: Gemma 3 27B — $0.08/M, score 10.1 OpenAI: o3 Mini High — $1.1/M, score 16.3 DeepSeek-R1 — $0.7/M, score 24.6 o1 — $15/M, score 39.7 Meta: Llama 3.3 70B Instruct — $0.1/M, score 11.9 Meta: Llama 3.1 8B Instruct — $0.05/M, score 5.4 GPT-4o mini — $0.15/M, score 11.4 GPT-4o (2024-05-13) — $5/M, score 24.2 GPT-4 Turbo — $10/M, score 21.5 GPT-4 — $30/M, score 13.1 GPT-3.5-turbo — $0.5/M, score 10.7 Muse Spark 1.1 — $1.25/M, score 71.3 Kimi K3 — $3/M, score 76.2 Inkling — $1.87/M, score 52.1 Gemini 3.6 Flash — $1.5/M, score 69.2 Gemini 3.5 Flash Lite — $0.3/M, score 49.3 Claude Opus 5 — $5/M, score 78.0 Google: Gemini 3.6 Flash (batch) — $0.375/M, score 69.2 Google: Gemini 3.5 Flash Lite (batch) — $0.15/M, score 49.3 Anthropic: Claude Sonnet 5 (batch) — $1/M, score 71.5 Anthropic: Claude Fable 5 (batch) — $5/M, score 76.5 MiniMax: MiniMax M3 (batch) — $0.15/M, score 58.6 Anthropic: Claude Opus 4.8 (batch) — $2.5/M, score 74.3 Google: Gemini 3.5 Flash (batch) — $0.75/M, score 70.1 OpenAI: GPT-5.5 (batch) — $2.5/M, score 74.9 Anthropic: Claude Opus 4.7 (batch) — $2.5/M, score 73.6 OpenAI: GPT-5.4 Nano (batch) — $0.1/M, score 56.1 OpenAI: GPT-5.4 Mini (batch) — $0.375/M, score 56.1 OpenAI: GPT-5.4 (batch) — $1.25/M, score 71.1 Google: Gemini 3.1 Pro Preview (batch) — $1/M, score 68.8 OpenAI: GPT-5.1 (batch) — $0.625/M, score 49.4 Anthropic: Claude Haiku 4.5 (batch) — $0.5/M, score 43.9 Anthropic: Claude Sonnet 4.5 (batch) — $1.5/M, score 52.1 OpenAI: GPT-5 (batch) — $0.625/M, score 37.8 OpenAI: GPT-5 Mini (batch) — $0.125/M, score 15.6 Google: Gemini 2.5 Pro (batch) — $0.625/M, score 33.3 DeepSeek V4 Flash 0731 — $0.08/M, score 69.1 Inkling Small — $0.45/M, score 52.9 DeepSeek V4 Pro 0813 — $0.435/M, score 68.8 Qwen: Qwen3.8 Max — $2/M, score 71.8 Ling-3.0-flash — $0.021/M, score 50.6 Claude Opus 5 (batch) — $2.5/M, score 78.0 Thinking Machines: Inkling (batch) — $0.5/M, score 52.1 OpenAI: GPT-5.6 Luna (batch) — $0.1/M, score 71.4 OpenAI: GPT-5.6 Terra (batch) — $1/M, score 76.7 OpenAI: GPT-5.6 Sol (batch) — $1.25/M, score 77.4 Z.ai: GLM 5.2 (batch) — $0.7/M, score 68.8 MoonshotAI: Kimi K2.7 Code (batch) — $0.475/M, score 60.8 NVIDIA: Nemotron 3 Ultra (batch) — $0.3/M, score 49.3 Anthropic: Claude Sonnet 4.6 (batch) — $1.5/M, score 63.0 OpenAI: GPT-4.1 Mini (batch) — $0.2/M, score 20.2 OpenAI: GPT-4.1 Nano (batch) — $0.05/M, score 11.1 OpenAI: o3 Mini High (batch) — $0.55/M, score 16.3 OpenAI: o1 (batch) — $7.5/M, score 39.7 OpenAI: GPT-4o-mini (batch) — $0.075/M, score 11.4 OpenAI: GPT-4 Turbo (batch) — $5/M, score 21.5 OpenAI: GPT-3.5 Turbo (batch) — $0.25/M, score 10.7 Solar Pro 4 — $0.3/M, score 52.7 Nemotron 3.5 Lightning 30B A3B — $0.05/M, score 26.8 SpaceXAI: Grok 4.6 — $2/M, score 76.8 Gemini 3.7 Flash — $0.75/M, score 76.1 Google: Gemini 3.7 Flash (batch) — $0.188/M, score 76.1 Gemini 3.7 Flash Input price per million tokens (log scale) Index

The stepped line is the efficient frontier: at each price, the best score available for that money or less. A model sitting on it is not being beaten by anything cheaper. Price is log-scaled because listed rates span four orders of magnitude. Only models with both a listed price and a score on this benchmark can appear.

Catalog activity

Change log

Field-level changes detected between successful source imports.

Full change log
Price Completion1.875 → 3.75
Price Prompt0.375 → 0.75
Price Completion3.75 → 1.875
Price Prompt0.75 → 0.375
Price Completion1.875 → 3.75
Price Prompt0.375 → 0.75
Price Completion3.75 → 1.875
Price Prompt0.75 → 0.375
Price Completion1.875 → 3.75
Price Prompt0.375 → 0.75
Provenance

Sources & verification

Every figure on this page traces back to one of these records.

Methodology
Last verified
Aug 17, 2026
Status
Source-linked
Confidence
Medium
Catalog source
Models.dev
Models.devcatalog ↗OpenRouter documentationprovider documentation ↗NanoGPT documentationprovider documentation ↗Requesty documentationprovider documentation ↗Kilo Gateway documentationprovider documentation ↗Merge Gateway documentationprovider documentation ↗Vercel AI Gateway documentationprovider documentation ↗LLM Gateway documentationprovider documentation ↗Google documentationprovider documentation ↗Vertex documentationprovider documentation ↗Eden AI documentationprovider documentation ↗CrossModel documentationprovider documentation ↗
Public API

Use this record

Fetch the complete source-linked model record. No key, no account, no rate-limited tier.

API documentation
Endpoint
GET https://www.modelbench.lol/api/v1/models/google/gemini-3.7-flash
curl
curl "https://www.modelbench.lol/api/v1/models/google/gemini-3.7-flash"
Common questions

Frequently asked questions

Answered directly from the stored record — nothing here is generated beyond the catalog's own fields.

What is Gemini 3.7 Flash?

High-efficiency Gemini model for agentic workflows, coding, and multimodal reasoning. It is published by Google and catalogued here from Models.dev.

How much does Gemini 3.7 Flash cost?

Listed input pricing starts at $0.375 per million tokens from OpenRouter, rising to $1.875 across 19 listed providers.

What is the context length of Gemini 3.7 Flash?

Gemini 3.7 Flash accepts up to 1.04858M tokens of context and returns up to 65.536K output tokens.

Does Gemini 3.7 Flash support tool calling and structured output?

Provider catalogs list support for tool calling, structured output, reasoning, and image input.

Which providers serve Gemini 3.7 Flash?

17 providers list this model: OpenRouter, NanoGPT, Requesty, Kilo Gateway, Merge Gateway, Vercel AI Gateway and 11 more.

Are the weights for Gemini 3.7 Flash open?

No. This model is served through hosted APIs only.

When was Gemini 3.7 Flash released?

The catalog records a release date of 2026-08-13, last verified Aug 17, 2026.

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