Noometry

Model comparison

GPT-5.3 Chat vs Mixtral 8x7B

GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 27.1 on the Noometry Index. Mixtral 8x7B costs 6.9× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.

Last verified . 17 shared benchmarks.

GPT-5.3 Chat OpenAI

42.8

Rank #109 Confirmed

Mixtral 8x7B Mistral AI

27.1

Rank #334 Confirmed

Summary

  • They share 17 benchmarks with published results for both. GPT-5.3 Chat scores higher in 8 categories and Mixtral 8x7B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where GPT-5.3 Chat leads 63.1 to 34.2.
  • Mixtral 8x7B is cheaper at $0.70 / $0.70 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Chat.
  • GPT-5.3 Chat accepts more context: 128K tokens versus 32K.
  • Mixtral 8x7B has downloadable open weights; the other is API-only.

Side by side

GPT-5.3 ChatMixtral 8x7B
ProviderOpenAIMistral AI
Noometry Index42.827.1
Released2026-03-032023-12-11
WeightsProprietaryOpen
Context window128K32K
Max output16K32K
Input $ / M tokens$1.75$0.70
Output $ / M tokens$14$0.70
Results tracked1838

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

Category by category

Coding GPT-5.3 Chat leads

GPT-5.3 Chat: 41.4 (#124), Mixtral 8x7B: 32.8 (#269)

BenchmarkGPT-5.3 ChatMixtral 8x7B
LMArena Coding14081126
HumanEval+—39.6%
MBPP+—49.7%

Reasoning GPT-5.3 Chat leads

GPT-5.3 Chat: 28.5 (#102), Mixtral 8x7B: 18.2 (#285)

BenchmarkGPT-5.3 ChatMixtral 8x7B
LMArena Hard Prompts13991115
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 GPT-5.3 Chat leads

GPT-5.3 Chat: 38.2 (#142), Mixtral 8x7B: 18.8 (#289)

BenchmarkGPT-5.3 ChatMixtral 8x7B
LMArena Math13891147
Omni-MATH—10.5%
MATH Level 5—10%
GSM8K—74.4%

Knowledge GPT-5.3 Chat leads

GPT-5.3 Chat: 38.8 (#140), Mixtral 8x7B: 11.0 (#301)

BenchmarkGPT-5.3 ChatMixtral 8x7B
LMArena Expert13971088
GPQA Diamond—30.6%
MMLU-Pro—33.5%
GPQA (HELM)—29.6%
ARC (AI2) Challenge—87.3%
MMLU—70.6%
OpenBookQA—85.8%
TriviaQA—82.2%

Multilingual GPT-5.3 Chat leads

GPT-5.3 Chat: 50.3 (#124), Mixtral 8x7B: 29.6 (#266)

BenchmarkGPT-5.3 ChatMixtral 8x7B
LMArena Non-English13821077
LMArena Chinese14321055
LMArena French13971166
LMArena German13841114
LMArena Japanese1352931
LMArena Korean1346968
LMArena Russian14001090
LMArena Spanish13711111

Instruction Following GPT-5.3 Chat leads

GPT-5.3 Chat: 72.8 (#129), Mixtral 8x7B: 51.0 (#297)

BenchmarkGPT-5.3 ChatMixtral 8x7B
LMArena Instruction Following13781109
IFEval—57.5%

Long Context GPT-5.3 Chat leads

GPT-5.3 Chat: 42.6 (#120), Mixtral 8x7B: 33.4 (#260)

BenchmarkGPT-5.3 ChatMixtral 8x7B
LMArena Longer Query13961103

Writing & Preference GPT-5.3 Chat leads

GPT-5.3 Chat: 63.1 (#68), Mixtral 8x7B: 34.2 (#270)

BenchmarkGPT-5.3 ChatMixtral 8x7B
LMArena Text13891132
LMArena Creative Writing13551109
LMArena Multi-Turn14121115
EQ-Bench Creative Writing1690—
WildBench—67.3%

Frequently asked questions

Is GPT-5.3 Chat better than Mixtral 8x7B?

GPT-5.3 Chat is the stronger model overall, scoring 42.8 to 27.1 on the Noometry Index. Mixtral 8x7B costs 6.9× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.

Which is cheaper, GPT-5.3 Chat or Mixtral 8x7B?

Mixtral 8x7B is cheaper. It lists at $0.70 per million input tokens and $0.70 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.

Is GPT-5.3 Chat or Mixtral 8x7B better for coding?

GPT-5.3 Chat scores higher on coding benchmarks: 41.4 versus 32.8 in the Noometry coding category.

Which has the bigger context window?

GPT-5.3 Chat does, with 128K tokens against 32K.

How many benchmarks do GPT-5.3 Chat and Mixtral 8x7B share?

17 benchmarks have published results for both models. GPT-5.3 Chat has 18 scored results on Noometry and Mixtral 8x7B has 38.

Related comparisons

Go deeper