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text model comparison

Gemini 3.7 Flash vs Grok 4.3

Gemini 3.7 Flash and Grok 4.3 are both current text models, from Google and xAI. Gemini 3.7 Flash is 40% cheaper per 1M input tokens than Grok 4.3, $0.75 vs $1.25. On Arena Text, Gemini 3.7 Flash scores 1486 Elo and Grok 4.3 1442 Elo (Arena, measured October 8, 2026). Both accept about 1.05M tokens of context (1,048,576 and 1,000,000).

Higher Arena Text
Gemini 3.7 Flash1486 Elo against 1442 Elo
Lower price per 1M input tokens
Gemini 3.7 Flash$0.75 against $1.25
Longer context window
Gemini 3.7 Flash1.05M tokens against 1M tokens

Data verified October 12, 2026 · Dataset 2026-10-28

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Side by side

Gemini 3.7 Flash and Grok 4.3, line by line

Prices in effect today, compared at the same tier wherever both list one. The better value in each row is highlighted.

FactGemini 3.7 FlashGrok 4.3
Price
Price per 1M input tokens$0.75 (better)$1.25
Price per 1M output tokens$3.75$2.50 (better)
Independent benchmarks
Arena Text1486 Elo (#10 of 49) (better)1442 Elo (#39 of 49)
GPQA Diamond94.8% (#5 of 40) (better)88.8% (#32 of 40)
FrontierMath Tiers 1-3 (v2)71.6% (#20 of 40) (better)42.8% (#35 of 40)
SimpleQA Verified69.2% (#9 of 36) (better)33.2% (#30 of 36)
Specs
ProviderGooglexAI
Release dateAugust 13, 2026Not reported
AccessAPI onlyAPI only
Context window1,048,576 tokens1,000,000 tokens
Max output65,536 tokensNot reported
Inputtext, image, audio, videotext, image
Outputtexttext

Scores:Arena · 2026-10-12Epoch AI · 2026-10-12

Open both in the interactive comparison

Charts

Against every current text model

Where Gemini 3.7 Flash and Grok 4.3 land among the current models of their task, on every independent benchmark, on price and on context.

Where each stands

On Arena Text, Gemini 3.7 Flash ranks #10 and Grok 4.3 #39 of 49 current models. Each bar is the share of current models it beats: on score, price and context.

Gemini 3.7 Flash and Grok 4.3 among the current text models, one row per benchmark, price and context window.

Independent benchmarks

Arena Text

Gemini 3.7 Flash:#10of 49

1,486 Elo · ahead of 81%

Grok 4.3:#39of 49

1,442 Elo · ahead of 21%

GPQA Diamond

Gemini 3.7 Flash:#5of 40

94.8% · ahead of 90%

Grok 4.3:#32of 40

88.8% · ahead of 21%

FrontierMath Tiers 1-3 (v2)

Gemini 3.7 Flash:#20of 40

71.6% · ahead of 51%

Grok 4.3:#35of 40

42.8% · ahead of 13%

SimpleQA Verified

Gemini 3.7 Flash:#9of 36

69.2% · ahead of 77%

Grok 4.3:#30of 36

33.2% · ahead of 17%

Price and context

Price per 1M input tokens

Gemini 3.7 Flash:#17of 51

$0.75 · cheaper than 66%

Grok 4.3:#21of 51

$1.25 · cheaper than 56%

Price per 1M output tokens

Gemini 3.7 Flash:#20of 51

$3.75 · cheaper than 60%

Grok 4.3:#15of 51

$2.50 · cheaper than 68%

Context window

Gemini 3.7 Flash:#11of 66

1.05M tokens · longer than 65%

Grok 4.3:#28of 66

1M tokens · longer than 22%

Quality against price

Arena Text · measured October 8, 2026

Gemini 3.7 Flash scores 1,486 at $1.50; Grok 4.3 scores 1,442 at $1.56 (blended price per 1M tokens). The line joins the current models no other beats on both price and Arena Text score; hover any point to name it.

Quality against priceArena Text score against price for 41 text models, Gemini 3.7 Flash and Grok 4.3 marked.1,2501,3001,3501,4001,4501,5001,550$0.30$1$3$10MOST ATTRACTIVE QUADRANTMedian price $3Median 1,475Blended price per 1M tokens (3 input : 1 output), log scaleArena Text (Elo)Gemini 3.7 FlashGrok 4.3
Quality against price: the data
Arena Text score against price for 41 text models, Gemini 3.7 Flash and Grok 4.3 marked.
ModelProviderBlended price per 1M tokensArena Text (Elo)
Gemini 4 ArgonGoogle$41,525
Claude Opus 5.5Anthropic$81,507
Claude Fable 5Anthropic$201,504
Claude Fable 5.1Anthropic$201,501
Gemini 3.8 FlashGoogle$1.501,497
Muse Spark 1.3Meta$21,494
Claude Opus 5Anthropic$101,490
Kimi K3Moonshot Kimi$61,488
Gemini 3.7 FlashGoogle$1.501,486
GPT-5.6 SolOpenAI$81,485
GPT-6.1 SolOpenAI$41,484
Qwen3.8-MaxAlibaba Qwen$31,483
GPT-5.5OpenAI$111,482
Gemini 3.6 FlashGoogle$31,482
Claude Opus 4.8Anthropic$101,481
MiMo-V2.6-ProXiaomi MiMo$0.541,480
GLM-5.3Z.ai$2.151,478
Claude Sonnet 5.5Anthropic$41,476
GPT-5.4OpenAI$5.631,475
GPT-6 AstraOpenAI$201,475
DeepSeek-V4.1-FlashDeepSeek$0.521,475
GLM-5.3-FlashZ.ai$0.241,475
Gemini 3 Flash PreviewGoogle$1.131,473
Grok 4.20xAI$1.561,472
GPT-5.6 TerraOpenAI$4.501,466
Grok 4.5xAI$31,466
DeepSeek-V4-ProDeepSeek$1.981,465
Claude Sonnet 5Anthropic$41,461
GPT-6 SolOpenAI$41,456
Gemini 3.5 Flash-LiteGoogle$0.851,455
Grok 4.6xAI$31,454
GPT-5.6 LunaOpenAI$0.451,452
MiMo-V2.6-FlashXiaomi MiMo$0.181,451
GPT-6 LunaOpenAI$0.201,443
Grok 4.7xAI$31,443
Grok 4.3xAI$1.561,442
Mistral Large 4Mistral AI$2.061,429
GPT-4.1OpenAI$3.501,415
Solar Pro 4Upstage$0.521,386
GPT-4.1 miniOpenAI$0.701,383
GPT-4.1 nanoOpenAI$0.181,322

Cost

What each costs

Example workloads at each provider's listed rates, then every other rate either one lists. The cheaper figure in each row is highlighted.

The same work, priced

For 10M input and 2M output tokens, Grok 4.3 costs 1.2 times as much as Gemini 3.7 Flash, at each provider's listed rates.

What Gemini 3.7 Flash and Grok 4.3cost for the same work, at each provider's listed rates.
  • 10M input and 2M output tokens

    Grok 4.3 costs 1.2× as much

    Gemini 3.7 Flash
    $15
    Grok 4.3
    $17.50
Workload or rateGemini 3.7 FlashGrok 4.3
Example workloads
10M input and 2M output tokens$15 (better)$17.50
The same, with 9M of the input tokens cachedNot listed$8.05
Other listed rates
1M input tokens, cachedNot listed$0.20

Verdict

When to choose each

Gemini 3.7 Flash

Where it leads

  • Lower price per 1M input tokens, $0.75 vs $1.25
  • Lower cost for 10M input and 2M output tokens, $15 vs $17.50
  • Higher Arena Text score, 1486 Elo vs 1442 Elo
  • Higher GPQA Diamond score, 94.8% vs 88.8%
  • Higher FrontierMath Tiers 1-3 (v2) score, 71.6% vs 42.8%
  • Higher SimpleQA Verified score, 69.2% vs 33.2%
  • Accepts audio and video input

Best for

  • Production coding and agent workflows that need multimodal context

Watch out for

  • Google publishes the introductory API price through 2026-12-31; standard input and output prices increase on 2027-01-01.
  • Not in the pinned LiveBench snapshot; its independent scores here come from Epoch AI's own GPQA Diamond, FrontierMath and SimpleQA Verified runs

Grok 4.3

Where it leads

  • Lower price per 1M output tokens, $2.50 vs $3.75
  • A cached-input rate, $0.20 per 1M tokens

Best for

  • General-purpose reasoning, instruction following, and agentic tool-use evaluations

Watch out for

  • The published base rates double when requests reach the provider's 200,000-token long-context threshold

From benchmark to production

Building on Gemini 3.7 Flash or Grok 4.3?

Public scores rarely hold on your own data. We test both models on your real tasks, then build the agent or pipeline around the one that wins.

FAQ

Gemini 3.7 Flash vs Grok 4.3 FAQ

Which is cheaper, Gemini 3.7 Flash or Grok 4.3?

Gemini 3.7 Flash is 40% cheaper per 1M input tokens than Grok 4.3, $0.75 vs $1.25. For 10M input and 2M output tokens, Gemini 3.7 Flash costs $15 and Grok 4.3 $17.50 at standard rates.

Do Gemini 3.7 Flash and Grok 4.3 discount cached input?

Grok 4.3 lists a cached-input rate of $0.20 per 1M tokens, 84% below its standard input rate. No cached-input rate is listed for Gemini 3.7 Flash.

Which scores higher on independent benchmarks, Gemini 3.7 Flash or Grok 4.3?

Gemini 3.7 Flash leads on Arena Text, 1486 Elo to 1442 Elo; Gemini 3.7 Flash leads on GPQA Diamond, 94.8% to 88.8%; Gemini 3.7 Flash leads on FrontierMath Tiers 1-3 (v2), 71.6% to 42.8%. Scores are independent evaluations, not either vendor's launch figures.

Which has the larger context window, Gemini 3.7 Flash or Grok 4.3?

Both accept about 1.05M tokens of context (1,048,576 and 1,000,000).

How do Gemini 3.7 Flash and Grok 4.3 differ in features?

Gemini 3.7 Flash takes text, image, audio and video input; Grok 4.3 takes text and image.

Production evaluation

Choosing between Gemini 3.7 Flash and Grok 4.3?

Public benchmarks narrow the shortlist. We run both on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.

  • A head-to-head evaluation on your real workload
  • Routing between models by cost and difficulty