Noometry

Model comparison

GPT-6 Luna vs Mixtral 8x22B

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 8x22B Mistral AI

27.1

Rank #333 Confirmed

Summary

  • They share 20 benchmarks with published results for both. GPT-6 Luna scores higher in 9 categories and Mixtral 8x22B in 0 categories; 9 gaps are clear of the uncertainty.
  • The widest gap is in math, where GPT-6 Luna leads 76.1 to 22.9.
  • The biggest single-benchmark swing is GPQA Diamond: 90.5% for GPT-6 Luna and 34.1% for Mixtral 8x22B.
  • GPT-6 Luna is cheaper at $0.10 / $0.50 per million input/output tokens, against $2 / $6 for Mixtral 8x22B.
  • GPT-6 Luna accepts more context: 1.05M tokens versus 64K.
  • Mixtral 8x22B has downloadable open weights; the other is API-only.

Side by side

GPT-6 LunaMixtral 8x22B
ProviderOpenAIMistral AI
Noometry Index53.327.1
Released2026-09-222024-04-17
WeightsProprietaryOpen
Context window1.05M64K
Max output128K64K
Input $ / M tokens$0.10$2
Output $ / M tokens$0.50$6
Results tracked4234

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

Category by category

Coding GPT-6 Luna leads

GPT-6 Luna: 55.5 (#25), Mixtral 8x22B: 24.2 (#329)

BenchmarkGPT-6 LunaMixtral 8x22B
LMArena Coding14391166
DeepSWE66.6%—
FrontierCode42.4%—
LMArena WebDev1581—
SciCode54.6%—
WeirdML—3.2%
BigCodeBench Instruct—40.6%
BigCodeBench Complete—50.2%
ALE-Bench1,577—
HumanEval+—72%
MBPP+—64.3%

Agentic & Tool Use GPT-6 Luna leads

GPT-6 Luna: 33.3 (#54), Mixtral 8x22B: 23.1 (#127)

BenchmarkGPT-6 LunaMixtral 8x22B
APEX-Agents44.3%—
Cybench—7.5%
GDP.pdf23%—

Reasoning GPT-6 Luna leads

GPT-6 Luna: 48.2 (#41), Mixtral 8x22B: 19.9 (#248)

BenchmarkGPT-6 LunaMixtral 8x22B
LMArena Hard Prompts14111150
DTBench90.1%55.1%
Epoch Capabilities Index156.28122.03
ARC-AGI-259.3%—
NYT Connections (extended)68.7%—
ARC-AGI-186.7%—
CritPt19.4%—
Chess Puzzles31%—
Mystery Game Puzzles7%—
LMCA44.5%—
ForecastBench—56.3

Math GPT-6 Luna leads

GPT-6 Luna: 76.1 (#15), Mixtral 8x22B: 22.9 (#275)

BenchmarkGPT-6 LunaMixtral 8x22B
LMArena Math14161184
FrontierMath (Tiers 1-3)78.9%—
FrontierMath Tier 456.1%—
OTIS Mock AIME 2024-202598.9%—
ProofBench64%—
Omni-MATH—16.3%
MATH Level 5—24.2%

Knowledge GPT-6 Luna leads

GPT-6 Luna: 57.0 (#41), Mixtral 8x22B: 15.1 (#293)

BenchmarkGPT-6 LunaMixtral 8x22B
GPQA Diamond90.5%34.1%
LMArena Expert14441113
SimpleQA Verified41.4%—
MMLU-Pro—46%
GPQA (HELM)—33.4%
MMLU—77.8%

Multimodal Not comparable

GPT-6 Luna: 42.4 (#30), Mixtral 8x22B: —

BenchmarkGPT-6 LunaMixtral 8x22B
LMArena Vision1217—
Blueprint-Bench 231.2%—
Furniture Assembly44.2%—

Multilingual GPT-6 Luna leads

GPT-6 Luna: 50.5 (#117), Mixtral 8x22B: 32.8 (#255)

BenchmarkGPT-6 LunaMixtral 8x22B
LMArena Non-English13861128
LMArena Chinese14331116
LMArena French14201166
LMArena German13691141
LMArena Japanese13691037
LMArena Korean13601057
LMArena Russian13941158
LMArena Spanish13931151

Instruction Following GPT-6 Luna leads

GPT-6 Luna: 74.3 (#99), Mixtral 8x22B: 57.7 (#266)

BenchmarkGPT-6 LunaMixtral 8x22B
LMArena Instruction Following14091147
IFEval—72.4%

Long Context GPT-6 Luna leads

GPT-6 Luna: 43.0 (#111), Mixtral 8x22B: 34.7 (#247)

BenchmarkGPT-6 LunaMixtral 8x22B
LMArena Longer Query14091144

Writing & Preference GPT-6 Luna leads

GPT-6 Luna: 58.3 (#119), Mixtral 8x22B: 36.9 (#262)

BenchmarkGPT-6 LunaMixtral 8x22B
LMArena Text13911162
LMArena Creative Writing13631141
LMArena Multi-Turn13961130
WildBench—71.1%

Frequently asked questions

Is GPT-6 Luna better than Mixtral 8x22B?

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 8x22B?

GPT-6 Luna is cheaper. It lists at $0.10 per million input tokens and $0.50 per million output tokens; Mixtral 8x22B lists at $2 and $6.

Is GPT-6 Luna or Mixtral 8x22B better for coding?

GPT-6 Luna scores higher on coding benchmarks: 55.5 versus 24.2 in the Noometry coding category.

Which has the bigger context window?

GPT-6 Luna does, with 1.05M tokens against 64K.

How many benchmarks do GPT-6 Luna and Mixtral 8x22B share?

20 benchmarks have published results for both models. GPT-6 Luna has 42 scored results on Noometry and Mixtral 8x22B has 34.

Related comparisons

Go deeper