Noometry

Model comparison

GPT-6 Luna vs Qwen3.5-Flash

GPT-6 Luna is the stronger model overall, scoring 45.1 to 42.3 on the Noometry Index.

Last verified . 14 shared benchmarks.

GPT-6 Luna OpenAI

45.1

Rank #65 Confirmed

Qwen3.5-Flash Alibaba (Qwen)

42.3

Rank #105 Confirmed

Summary

  • They share 14 benchmarks with published results for both. GPT-6 Luna scores higher in 5 categories and Qwen3.5-Flash in 3 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in coding, where GPT-6 Luna leads 54.7 to 33.9.
  • Qwen3.5-Flash is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.10 / $0.50 for GPT-6 Luna.
  • GPT-6 Luna accepts more context: 1.05M tokens versus 1M.

Side by side

GPT-6 LunaQwen3.5-Flash
ProviderOpenAIAlibaba (Qwen)
Noometry Index45.142.3
Released2026-09-222026-02-23
WeightsProprietaryProprietary
Context window1.05M1M
Max output128K66K
Input $ / M tokens$0.10$0.10
Output $ / M tokens$0.50$0.40
Results tracked1832

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Category by category

Coding GPT-6 Luna leads

GPT-6 Luna: 54.7 (#24), Qwen3.5-Flash: 33.9 (#234)

BenchmarkGPT-6 LunaQwen3.5-Flash
LMArena WebDev15831243
LMArena Coding14481412
DeepSWE66.6%—
FrontierCode42.4%—
ALE-Bench—221.8

Agentic & Tool Use Not comparable

GPT-6 Luna: —, Qwen3.5-Flash: —

BenchmarkGPT-6 LunaQwen3.5-Flash
Vending-Bench 2—462.69

Reasoning Qwen3.5-Flash leads

GPT-6 Luna: 31.7 (#68), Qwen3.5-Flash: 32.9 (#63)

BenchmarkGPT-6 LunaQwen3.5-Flash
LMArena Hard Prompts14151404
NYT Connections (extended)68.7%—
Chess Puzzles—21%
Mystery Game Puzzles—20%
DTBench—82.9%
LMCA—29.1%
Epoch Capabilities Index—143.98

Math Too close to call

GPT-6 Luna: 35.6 (#140), Qwen3.5-Flash: 36.3 (#117)

BenchmarkGPT-6 LunaQwen3.5-Flash
LMArena Math13961407
FrontierMath (Tiers 1-3)—18.2%
OTIS Mock AIME 2024-2025—84.4%
FrontierMath (Feb 2025 set)—6.2%
FrontierMath Tier 4 (v1)—0%

Knowledge Qwen3.5-Flash leads

GPT-6 Luna: 40.1 (#110), Qwen3.5-Flash: 43.2 (#84)

BenchmarkGPT-6 LunaQwen3.5-Flash
LMArena Expert14581408
GPQA Diamond—82.3%
SimpleQA Verified—20.3%
Vectara Hallucination Rate—10.5%

Multimodal Not comparable

GPT-6 Luna: 42.0 (#27), Qwen3.5-Flash: —

BenchmarkGPT-6 LunaQwen3.5-Flash
Furniture Assembly44.2%—

Multilingual Too close to call

GPT-6 Luna: 51.0 (#111), Qwen3.5-Flash: 50.7 (#116)

BenchmarkGPT-6 LunaQwen3.5-Flash
LMArena Non-English13901385
LMArena Chinese14251446
LMArena Russian13921379
LMArena Spanish14161399
LMArena French—1412
LMArena German—1389
LMArena Japanese—1369
LMArena Korean—1344

Instruction Following GPT-6 Luna leads

GPT-6 Luna: 74.7 (#85), Qwen3.5-Flash: 72.8 (#133)

BenchmarkGPT-6 LunaQwen3.5-Flash
LMArena Instruction Following14141374

Long Context Too close to call

GPT-6 Luna: 43.3 (#95), Qwen3.5-Flash: 42.4 (#119)

BenchmarkGPT-6 LunaQwen3.5-Flash
LMArena Longer Query14171392

Writing & Preference Too close to call

GPT-6 Luna: 58.4 (#115), Qwen3.5-Flash: 58.2 (#117)

BenchmarkGPT-6 LunaQwen3.5-Flash
LMArena Text13921397
LMArena Creative Writing13571343
LMArena Multi-Turn14001393

Frequently asked questions

Is GPT-6 Luna better than Qwen3.5-Flash?

GPT-6 Luna is the stronger model overall, scoring 45.1 to 42.3 on the Noometry Index.

Which is cheaper, GPT-6 Luna or Qwen3.5-Flash?

Qwen3.5-Flash is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; GPT-6 Luna lists at $0.10 and $0.50.

Is GPT-6 Luna or Qwen3.5-Flash better for coding?

GPT-6 Luna scores higher on coding benchmarks: 54.7 versus 33.9 in the Noometry coding category.

Which has the bigger context window?

GPT-6 Luna does, with 1.05M tokens against 1M.

How many benchmarks do GPT-6 Luna and Qwen3.5-Flash share?

14 benchmarks have published results for both models. GPT-6 Luna has 18 scored results on Noometry and Qwen3.5-Flash has 32.

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