Model comparison

GPT-5-Codex vs Mixtral 8x7B

GPT-5-Codex is the stronger model overall, scoring 37.9 to 27.1 on the Noometry Index. Mixtral 8x7B costs 4.9× less per token, which makes it the better buy when GPT-5-Codex's lead doesn't matter for your workload.

Last verified . 0 shared benchmarks.

GPT-5-Codex OpenAI

37.9

Rank #192 Reported

Mixtral 8x7B Mistral AI

27.1

Rank #334 Confirmed

Summary

  • The widest gap is in reasoning, where GPT-5-Codex leads 30.9 to 18.2.
  • Mixtral 8x7B is cheaper at $0.70 / $0.70 per million input/output tokens, against $1.25 / $10 for GPT-5-Codex.
  • GPT-5-Codex accepts more context: 400K tokens versus 32K.
  • Mixtral 8x7B has downloadable open weights; the other is API-only.

Side by side

GPT-5-Codex and Mixtral 8x7B specifications
GPT-5-CodexMixtral 8x7B
ProviderOpenAIMistral AI
Noometry Index37.927.1
Released2025-09-152023-12-11
WeightsProprietaryOpen
Context window400K32K
Max output128K32K
Input $ / M tokens$1.25$0.70
Output $ / M tokens$10$0.70
Results tracked338

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Category by category

Coding GPT-5-Codex leads

GPT-5-Codex: 42.4 (#103), Mixtral 8x7B: 32.8 (#269)

Coding benchmarks
BenchmarkGPT-5-CodexMixtral 8x7B
WeirdML54.5%—
LMArena Coding—1126
HumanEval+—39.6%
MBPP+—49.7%

Agentic & Tool Use Not comparable

GPT-5-Codex: 31.0 (#72), Mixtral 8x7B: —

Agentic & Tool Use benchmarks
BenchmarkGPT-5-CodexMixtral 8x7B
Terminal-Bench44.3%—

Reasoning GPT-5-Codex leads

GPT-5-Codex: 30.9 (#83), Mixtral 8x7B: 18.2 (#285)

Reasoning benchmarks
BenchmarkGPT-5-CodexMixtral 8x7B
Kagi LLM Benchmark70.3%—
LMArena Hard Prompts—1115
DTBench—49.6%
Adversarial NLI—55.2%
Epoch Capabilities Index—118.47
ForecastBench—56.3
HellaSwag—86.7%
PIQA—83.6%
WinoGrande—77.2%

Math Not comparable

GPT-5-Codex: —, Mixtral 8x7B: 18.8 (#289)

Math benchmarks
BenchmarkGPT-5-CodexMixtral 8x7B
Omni-MATH—10.5%
LMArena Math—1147
MATH Level 5—10%
GSM8K—74.4%

Knowledge Not comparable

GPT-5-Codex: —, Mixtral 8x7B: 11.0 (#301)

Knowledge benchmarks
BenchmarkGPT-5-CodexMixtral 8x7B
GPQA Diamond—30.6%
MMLU-Pro—33.5%
GPQA (HELM)—29.6%
LMArena Expert—1088
ARC (AI2) Challenge—87.3%
MMLU—70.6%
OpenBookQA—85.8%
TriviaQA—82.2%

Multilingual Not comparable

GPT-5-Codex: —, Mixtral 8x7B: 29.6 (#266)

Multilingual benchmarks
BenchmarkGPT-5-CodexMixtral 8x7B
LMArena Non-English—1077
LMArena Chinese—1055
LMArena French—1166
LMArena German—1114
LMArena Japanese—931
LMArena Korean—968
LMArena Russian—1090
LMArena Spanish—1111

Instruction Following Not comparable

GPT-5-Codex: —, Mixtral 8x7B: 51.0 (#297)

Instruction Following benchmarks
BenchmarkGPT-5-CodexMixtral 8x7B
IFEval—57.5%
LMArena Instruction Following—1109

Long Context Not comparable

GPT-5-Codex: —, Mixtral 8x7B: 33.4 (#260)

Long Context benchmarks
BenchmarkGPT-5-CodexMixtral 8x7B
LMArena Longer Query—1103

Writing & Preference Not comparable

GPT-5-Codex: —, Mixtral 8x7B: 34.2 (#270)

Writing & Preference benchmarks
BenchmarkGPT-5-CodexMixtral 8x7B
LMArena Text—1132
LMArena Creative Writing—1109
WildBench—67.3%
LMArena Multi-Turn—1115

Frequently asked questions

Is GPT-5-Codex better than Mixtral 8x7B?

GPT-5-Codex is the stronger model overall, scoring 37.9 to 27.1 on the Noometry Index. Mixtral 8x7B costs 4.9× less per token, which makes it the better buy when GPT-5-Codex's lead doesn't matter for your workload.

Which is cheaper, GPT-5-Codex or Mixtral 8x7B?

Mixtral 8x7B is cheaper. It lists at $0.70 per million input tokens and $0.70 per million output tokens; GPT-5-Codex lists at $1.25 and $10.

Is GPT-5-Codex or Mixtral 8x7B better for coding?

GPT-5-Codex scores higher on coding benchmarks: 42.4 versus 32.8 in the Noometry coding category.

Which has the bigger context window?

GPT-5-Codex does, with 400K tokens against 32K.

How many benchmarks do GPT-5-Codex and Mixtral 8x7B share?

0 benchmarks have published results for both models. GPT-5-Codex has 3 scored results on Noometry and Mixtral 8x7B has 38.

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