Noometry

Model comparison

Gemini 3.7 Flash vs GPT-5-Codex

Gemini 3.7 Flash is the stronger model overall, scoring 59.8 to 37.9 on the Noometry Index.

Last verified . 0 shared benchmarks.

Gemini 3.7 Flash Google

59.8

Rank #14 Confirmed

GPT-5-Codex OpenAI

37.9

Rank #192 Reported

Summary

  • The widest gap is in reasoning, where Gemini 3.7 Flash leads 70.0 to 30.9.
  • Gemini 3.7 Flash is cheaper at $0.75 / $3.75 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
  • Gemini 3.7 Flash accepts more context: 1.05M tokens versus 400K.

Side by side

Gemini 3.7 FlashGPT-5-Codex
ProviderGoogleOpenAI
Noometry Index59.837.9
Released2026-08-132025-09-15
WeightsProprietaryProprietary
Context window1.05M400K
Max output66K128K
Input $ / M tokens$0.75$1.25
Output $ / M tokens$3.75$10
Results tracked443

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding Gemini 3.7 Flash leads

Gemini 3.7 Flash: 56.2 (#22), GPT-5-Codex: 42.4 (#103)

BenchmarkGemini 3.7 FlashGPT-5-Codex
DeepSWE65.5%—
FrontierCode43.6%—
LMArena WebDev1592—
FrontierSWE20.3%—
SciCode59.8%—
WeirdML—54.5%
LMArena Coding1497—
ALE-Bench904.3—

Agentic & Tool Use Gemini 3.7 Flash leads

Gemini 3.7 Flash: 42.1 (#19), GPT-5-Codex: 31.0 (#72)

BenchmarkGemini 3.7 FlashGPT-5-Codex
Terminal-Bench—44.3%
APEX-Agents67.8%—
Remote Labor Index5%—
GDP.pdf23.8%—

Reasoning Gemini 3.7 Flash leads

Gemini 3.7 Flash: 70.0 (#15), GPT-5-Codex: 30.9 (#83)

BenchmarkGemini 3.7 FlashGPT-5-Codex
ARC-AGI-284.6%—
Kagi LLM Benchmark—70.3%
NYT Connections (extended)94%—
ARC-AGI-195.5%—
CritPt14.3%—
Chess Puzzles47%—
LMArena Hard Prompts1494—
Mystery Game Puzzles37%—
DTBench96.8%—
LMCA50.4%—
Epoch Capabilities Index157.27—

Math Not comparable

Gemini 3.7 Flash: 69.6 (#23), GPT-5-Codex: —

BenchmarkGemini 3.7 FlashGPT-5-Codex
FrontierMath (Tiers 1-3)71.6%—
FrontierMath Tier 436.6%—
OTIS Mock AIME 2024-202597.2%—
ProofBench58%—
LMArena Math1507—

Knowledge Not comparable

Gemini 3.7 Flash: 69.7 (#5), GPT-5-Codex: —

BenchmarkGemini 3.7 FlashGPT-5-Codex
GPQA Diamond94.8%—
SimpleQA Verified69.2%—
LMArena Expert1508—

Multimodal Not comparable

Gemini 3.7 Flash: 37.3 (#73), GPT-5-Codex: —

BenchmarkGemini 3.7 FlashGPT-5-Codex
LMArena Vision1316—
Furniture Assembly26.7%—

Multilingual Not comparable

Gemini 3.7 Flash: 57.6 (#7), GPT-5-Codex: —

BenchmarkGemini 3.7 FlashGPT-5-Codex
LMArena Non-English1484—
LMArena Chinese1548—
LMArena French1505—
LMArena German1498—
LMArena Japanese1512—
LMArena Korean1483—
LMArena Russian1516—
LMArena Spanish1503—

Instruction Following Not comparable

Gemini 3.7 Flash: 77.7 (#15), GPT-5-Codex: —

BenchmarkGemini 3.7 FlashGPT-5-Codex
LMArena Instruction Following1483—

Long Context Not comparable

Gemini 3.7 Flash: 45.7 (#30), GPT-5-Codex: —

BenchmarkGemini 3.7 FlashGPT-5-Codex
LMArena Longer Query1492—

Writing & Preference Not comparable

Gemini 3.7 Flash: 71.2 (#20), GPT-5-Codex: —

BenchmarkGemini 3.7 FlashGPT-5-Codex
LMArena Text1486—
LMArena Creative Writing1490—
EQ-Bench Creative Writing1723—
LMArena Multi-Turn1489—

Frequently asked questions

Is Gemini 3.7 Flash better than GPT-5-Codex?

Gemini 3.7 Flash is the stronger model overall, scoring 59.8 to 37.9 on the Noometry Index.

Which is cheaper, Gemini 3.7 Flash or GPT-5-Codex?

Gemini 3.7 Flash is cheaper. It lists at $0.75 per million input tokens and $3.75 per million output tokens; GPT-5-Codex lists at $1.25 and $10.

Is Gemini 3.7 Flash or GPT-5-Codex better for coding?

Gemini 3.7 Flash scores higher on coding benchmarks: 56.2 versus 42.4 in the Noometry coding category.

Which has the bigger context window?

Gemini 3.7 Flash does, with 1.05M tokens against 400K.

How many benchmarks do Gemini 3.7 Flash and GPT-5-Codex share?

0 benchmarks have published results for both models. Gemini 3.7 Flash has 44 scored results on Noometry and GPT-5-Codex has 3.

Related comparisons

Go deeper