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Last scan 2026-09-27 Models tracked 271 Providers 35 Cheapest paid Granite 4.0 H Micro $0.017/Mtok in Every price links to its source

Gemini 3.7 Flash

by Google

Current Intro price flagship mid tier

Today's price · per 1M tokens

Input

$0.750

per 1M tokens

Output

$3.75

per 1M tokens

Blended

$1.50

blended $/1M — 3:1 weighted input:output

Cached input

$0.075

10% of input — prompt caching

How this price is scoped: Google's Gemini API pricing page prints a dated, two-phase schedule for this model: $0.75 per 1M input tokens through December 31, 2026, rising to $1.50 on January 1, 2027, and $3.75 per 1M output tokens through December 31, 2026, rising to $7.50. Context caching follows the same dates ($0.075, then $0.15). We publish the rate you would pay today and re-verify it before the changeover date. Note that resellers may quote a lower figure: OpenRouter's ':batch' route for this model now shows $0.375/$1.875, which is Google's own Batch tier — exactly half the standard rate, and not what an ordinary API call is billed. We publish the standard rate. Checked 2026-08-18 against ai.google.dev/gemini-api/docs/pricing; reseller routes re-checked 2026-09-02.

Source: official Google pricing · read MODELPRICEWATCH.COM · 2026-09-27

Price receipt

We read Google's own pricing page on and found Gemini 3.7 Flash listed with a price on the same card — that read is where the number above comes from. We keep the page text we read; its content hash is 60a63d484d.

Overview

Google's newest fast multimodal flagship, launched 2026-08-13 as the successor to Gemini 3.6 Flash — built for agentic workflows, coding and multi-step reasoning. Currently $0.75/1M input and $3.75/1M output on Google's dated schedule, reverting to $1.50/$7.50 on 2027-01-01. 1M-token context with native image, audio and video input.

Capabilities

struck through = not supported
Input 4/4
Text ✓ Image ✓ Audio ✓ Video ✓
Output
Text ✓
Features 4/9
Prompt caching ✓ Reasoning Coding Fast inference ✓ Long context ✓ Open weights Multimodal ✓ Web search Realtime

Benchmark performance

accuracy % · higher is better
Avg benchmark score80.3%
Perf per $/Mtok53.5
GPQA Diamond
93.9%
SWE-Bench Verified
80.8%
Terminal-Bench 2.1
85.8%
LiveCodeBench
88.7%
Humanity's Last Exam
47.9%
ARC-AGI 2
84.6%
AutoBench *
30.4%
Independent composite scores
  • AA Intelligence Index: 39.1 (Artificial Analysis composite across reasoning, knowledge and coding evals)
  • AA-Omniscience Index: 26.5 (−100–100)
  • GDPval-AA v2: 1516 ELO (Real-world work tasks, human baseline = 1000)
  • LMSYS Chatbot Arena: 1489.8 ELO (Human preference)
How it stacks up
  • Ranks #14 of 96 benchmarked models by average score
  • Ranks #21 of 187 comparably-measured models by percentile score, across 10 independent measurements
  • Ranks #52 of 187 comparably-tested models by normalized performance per dollar
  • Strongest at ARC-AGI 2 — 84.6%, #6 of 44

287.8 tokens/sec output

Source: Vellum LLM Leaderboard · updated · See full rankings →

Specifications

Provider
Google
Context window
1M tokens
Modality
text, image, audio, video
Parameters
Proprietary
Open source
No — proprietary
Released
Status
Current
Last updated
Tags
fastmultimodalflagship

Availability verified: — listed on Google's own page