Noometry

Model comparison

GPT-6 Luna vs Mixtral 8x7B

GPT-6 Luna is the stronger model overall, scoring 53.3 to 27.1 on the Noometry Index.

Last verified . 20 shared benchmarks.

GPT-6 Luna OpenAI

53.3

Rank #36 Confirmed

Mixtral 8x7B Mistral AI

27.1

Rank #334 Confirmed

Summary

  • They share 20 benchmarks with published results for both. GPT-6 Luna scores higher in 8 categories and Mixtral 8x7B in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in math, where GPT-6 Luna leads 76.1 to 18.8.
  • The biggest single-benchmark swing is GPQA Diamond: 90.5% for GPT-6 Luna and 30.6% for Mixtral 8x7B.
  • GPT-6 Luna is cheaper at $0.10 / $0.50 per million input/output tokens, against $0.70 / $0.70 for Mixtral 8x7B.
  • GPT-6 Luna accepts more context: 1.05M tokens versus 32K.
  • Mixtral 8x7B has downloadable open weights; the other is API-only.

Side by side

GPT-6 LunaMixtral 8x7B
ProviderOpenAIMistral AI
Noometry Index53.327.1
Released2026-09-222023-12-11
WeightsProprietaryOpen
Context window1.05M32K
Max output128K32K
Input $ / M tokens$0.10$0.70
Output $ / M tokens$0.50$0.70
Results tracked4238

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Category by category

Coding GPT-6 Luna leads

GPT-6 Luna: 55.5 (#25), Mixtral 8x7B: 32.8 (#269)

BenchmarkGPT-6 LunaMixtral 8x7B
LMArena Coding14391126
DeepSWE66.6%—
FrontierCode42.4%—
LMArena WebDev1581—
SciCode54.6%—
ALE-Bench1,577—
HumanEval+—39.6%
MBPP+—49.7%

Agentic & Tool Use Not comparable

GPT-6 Luna: 33.3 (#54), Mixtral 8x7B: —

BenchmarkGPT-6 LunaMixtral 8x7B
APEX-Agents44.3%—
GDP.pdf23%—

Reasoning GPT-6 Luna leads

GPT-6 Luna: 48.2 (#41), Mixtral 8x7B: 18.2 (#285)

BenchmarkGPT-6 LunaMixtral 8x7B
LMArena Hard Prompts14111115
DTBench90.1%49.6%
Epoch Capabilities Index156.28118.47
ARC-AGI-259.3%—
NYT Connections (extended)68.7%—
ARC-AGI-186.7%—
CritPt19.4%—
Chess Puzzles31%—
Mystery Game Puzzles7%—
LMCA44.5%—
Adversarial NLI—55.2%
ForecastBench—56.3
HellaSwag—86.7%
PIQA—83.6%
WinoGrande—77.2%

Math GPT-6 Luna leads

GPT-6 Luna: 76.1 (#15), Mixtral 8x7B: 18.8 (#289)

BenchmarkGPT-6 LunaMixtral 8x7B
LMArena Math14161147
FrontierMath (Tiers 1-3)78.9%—
FrontierMath Tier 456.1%—
OTIS Mock AIME 2024-202598.9%—
ProofBench64%—
Omni-MATH—10.5%
MATH Level 5—10%
GSM8K—74.4%

Knowledge GPT-6 Luna leads

GPT-6 Luna: 57.0 (#41), Mixtral 8x7B: 11.0 (#301)

BenchmarkGPT-6 LunaMixtral 8x7B
GPQA Diamond90.5%30.6%
LMArena Expert14441088
SimpleQA Verified41.4%—
MMLU-Pro—33.5%
GPQA (HELM)—29.6%
ARC (AI2) Challenge—87.3%
MMLU—70.6%
OpenBookQA—85.8%
TriviaQA—82.2%

Multimodal Not comparable

GPT-6 Luna: 42.4 (#30), Mixtral 8x7B: —

BenchmarkGPT-6 LunaMixtral 8x7B
LMArena Vision1217—
Blueprint-Bench 231.2%—
Furniture Assembly44.2%—

Multilingual GPT-6 Luna leads

GPT-6 Luna: 50.5 (#117), Mixtral 8x7B: 29.6 (#266)

BenchmarkGPT-6 LunaMixtral 8x7B
LMArena Non-English13861077
LMArena Chinese14331055
LMArena French14201166
LMArena German13691114
LMArena Japanese1369931
LMArena Korean1360968
LMArena Russian13941090
LMArena Spanish13931111

Instruction Following GPT-6 Luna leads

GPT-6 Luna: 74.3 (#99), Mixtral 8x7B: 51.0 (#297)

BenchmarkGPT-6 LunaMixtral 8x7B
LMArena Instruction Following14091109
IFEval—57.5%

Long Context GPT-6 Luna leads

GPT-6 Luna: 43.0 (#111), Mixtral 8x7B: 33.4 (#260)

BenchmarkGPT-6 LunaMixtral 8x7B
LMArena Longer Query14091103

Writing & Preference GPT-6 Luna leads

GPT-6 Luna: 58.3 (#119), Mixtral 8x7B: 34.2 (#270)

BenchmarkGPT-6 LunaMixtral 8x7B
LMArena Text13911132
LMArena Creative Writing13631109
LMArena Multi-Turn13961115
WildBench—67.3%

Frequently asked questions

Is GPT-6 Luna better than Mixtral 8x7B?

GPT-6 Luna is the stronger model overall, scoring 53.3 to 27.1 on the Noometry Index.

Which is cheaper, GPT-6 Luna or Mixtral 8x7B?

GPT-6 Luna is cheaper. It lists at $0.10 per million input tokens and $0.50 per million output tokens; Mixtral 8x7B lists at $0.70 and $0.70.

Is GPT-6 Luna or Mixtral 8x7B better for coding?

GPT-6 Luna scores higher on coding benchmarks: 55.5 versus 32.8 in the Noometry coding category.

Which has the bigger context window?

GPT-6 Luna does, with 1.05M tokens against 32K.

How many benchmarks do GPT-6 Luna and Mixtral 8x7B share?

20 benchmarks have published results for both models. GPT-6 Luna has 42 scored results on Noometry and Mixtral 8x7B has 38.

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