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GPT-6 Luna vs Qwen3.8 27B

Updated October 21, 2026. 71 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GPT-6 Luna Replace Qwen3.8 27B
GPT-6 LunaOpenAI
Coding
71.4
Overall
38.1
Output $/M
$0.50
24
Qwen3.8 27BQwen
Coding
73.6
Overall
33.7
Output $/M
$1.35
47
vs boards won of 71 shared

Decision reading

Pick Qwen3.8 27B for coding: it scores 73.6 on the Vibe Coding Index against 71.4 for GPT-6 Luna.

Pick GPT-6 Luna when output tokens cost 2.7x less, or when the context window is larger, 1.05M against 1M tokens.

Model AGPT-6 LunaOpenAI71.4/1002 independent benchmarksNo cost per solved taskModel BQwen3.8 27BQwen73.6/1002 independent benchmarks$1.26 per solved task
Shared results
71
GPT-6 Luna only
31
Qwen3.8 27B only
14
Like-for-like categories
8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
GPT-6 Luna 71.4 from 2 benchmarks, Qwen3.8 27B 73.6 from 2 benchmarks.
Widest category
Math, 20.3 points apart on average over 3 shared benchmarks.
Widest single gap
ProofBench: GPT-6 Luna 64.0% against Qwen3.8 27B 16.0%, 48.0 points apart on a 0 to 100 scale.
Output price
GPT-6 Luna $0.50 against Qwen3.8 27B $1.35 per million output tokens, 2.7x apart.
Context window
GPT-6 Luna takes 1.05M tokens, Qwen3.8 27B 1M.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryGPT-6 LunaBarsQwen3.8 27BTies
Coding86
Intelligence20
Agentic work54
Reasoning36
Math12
Knowledge14
Web design10
General325
All shared boards2447
CodingLike-for-likeFour of these boards feed the Vibe Coding Index86
Coding benchmarks for GPT-6 Luna and Qwen3.8 27B
BenchmarkGPT-6 LunaQwen3.8 27BLeader
LiveBench coding84.5%86.8%Qwen3.8 27B
LMArena WebDev15781593Qwen3.8 27B
AA Coding IndexNot measured68.1Only Qwen3.8 27B measured
LiveCodeBench (Vals AI)Not measured84.0%Only Qwen3.8 27B measured
SWE-bench Verified (Vals AI)Not measured86.0%Only Qwen3.8 27B measured
Terminal-Bench 4 (Vals AI)13.6%Not measuredOnly GPT-6 Luna measured
Vibe Code Bench (Vals AI)81.7%64.8%GPT-6 Luna
Code migration (Vals AI)42.5%14.2%GPT-6 Luna
ProgramBench (Vals AI)0.5%0.0%GPT-6 Luna
IOI (Vals AI)55.6%39.1%GPT-6 Luna
Terminal-Bench 2.1 (Vals AI)73.0%58.4%GPT-6 Luna
SWE-bench Multimodal (Vals AI)37.5%Not measuredOnly GPT-6 Luna measured
SkillsBench (Vals AI)Not measured38.1%Only Qwen3.8 27B measured
CyberBench (Vals AI)76.3%67.8%GPT-6 Luna
SciCode54.6%46.6%GPT-6 Luna
FrontierCode42.4%Not measuredOnly GPT-6 Luna measured
ALE-Bench1576.9Not measuredOnly GPT-6 Luna measured
LMArena Text: coding14371483Qwen3.8 27B
LMArena Text: software and IT14231478Qwen3.8 27B
LMArena WebDev: React15731602Qwen3.8 27B
LMArena WebDev: HTML15951570GPT-6 Luna
LMArena WebDev: from an image15711577Qwen3.8 27B
Neither model has a result on the other 16 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for GPT-6 Luna and Qwen3.8 27B
BenchmarkGPT-6 LunaQwen3.8 27BLeader
AA Intelligence Index38.133.7GPT-6 Luna
Epoch Capabilities Index156.8151.7GPT-6 Luna
Agentic workLike-for-likePublic boards, shown as published, kept out of the index54
Agentic work benchmarks for GPT-6 Luna and Qwen3.8 27B
BenchmarkGPT-6 LunaQwen3.8 27BLeader
AA Agentic IndexNot measured45.8Only Qwen3.8 27B measured
Design Arena: agents building web apps1189Not measuredOnly GPT-6 Luna measured
Design Arena: agents building full-stack apps1158Not measuredOnly GPT-6 Luna measured
Design Arena: agents building mobile apps1133Not measuredOnly GPT-6 Luna measured
LiveBench research43.5%59.4%Qwen3.8 27B
LiveBench browser72.0%32.0%GPT-6 Luna
LiveBench long agentic48.1%27.9%GPT-6 Luna
SREBench (Vals AI)2.7%Not measuredOnly GPT-6 Luna measured
Finance Agent (Vals AI)49.9%48.5%GPT-6 Luna
Tax Agent Bench (Vals AI)19.9%30.9%Qwen3.8 27B
Legal Research Bench (Vals AI)30.3%36.1%Qwen3.8 27B
Harvey's Legal Agent Benchmark (Vals AI)4.2%Not measuredOnly GPT-6 Luna measured
Excel Modeling Benchmark (Vals AI)68.5%59.7%GPT-6 Luna
BioMysteryBench (Vals AI)61.5%Not measuredOnly GPT-6 Luna measured
Terminal-Bench-Science (Vals AI)4.3%0.0%GPT-6 Luna
Vals Science Index28.4%Not measuredOnly GPT-6 Luna measured
APEX-Agents44.3%47.5%Qwen3.8 27B
SpireClimb0.0%Not measuredOnly GPT-6 Luna measured
Neither model has a result on the other 21 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index36
Reasoning benchmarks for GPT-6 Luna and Qwen3.8 27B
BenchmarkGPT-6 LunaQwen3.8 27BLeader
GPQA DiamondNot measured88.9%Only Qwen3.8 27B measured
LiveBench reasoning81.8%80.0%GPT-6 Luna
MysteryMechanism (Vals AI)19.4%Not measuredOnly GPT-6 Luna measured
MMMU Pro (Vals AI)Not measured83.9%Only Qwen3.8 27B measured
GPQA Diamond (Artificial Analysis run)Not measured90.5%Only Qwen3.8 27B measured
Humanity's Last Exam (Artificial Analysis run)38.5%33.9%GPT-6 Luna
GPQA Diamond (Epoch AI run)90.5%Not measuredOnly GPT-6 Luna measured
ARC-AGI86.7%87.5%Qwen3.8 27B
ARC-AGI-259.3%42.4%GPT-6 Luna
Chess puzzles36.0%Not measuredOnly GPT-6 Luna measured
Mystery game puzzles7.0%Not measuredOnly GPT-6 Luna measured
LMArena Text: hard prompts14101459Qwen3.8 27B
LMArena Text: expert14421479Qwen3.8 27B
LMArena Text: hard prompts in English14101461Qwen3.8 27B
LMArena Vision: diagrams12451285Qwen3.8 27B
LMArena Vision: homework12611295Qwen3.8 27B
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index12
Math benchmarks for GPT-6 Luna and Qwen3.8 27B
BenchmarkGPT-6 LunaQwen3.8 27BLeader
OTIS Mock AIME98.9%Not measuredOnly GPT-6 Luna measured
FrontierMath, tiers 1 to 378.9%Not measuredOnly GPT-6 Luna measured
FrontierMath, tier 456.1%Not measuredOnly GPT-6 Luna measured
ProofBench64.0%16.0%GPT-6 Luna
LMArena Text: math14091455Qwen3.8 27B
LMArena Text: mathematical work14271458Qwen3.8 27B
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index14
Knowledge benchmarks for GPT-6 Luna and Qwen3.8 27B
BenchmarkGPT-6 LunaQwen3.8 27BLeader
MMLU ProNot measured84.3%Only Qwen3.8 27B measured
LegalBench (Vals AI)Not measured82.4%Only Qwen3.8 27B measured
TaxEval (Vals AI)Not measured70.8%Only Qwen3.8 27B measured
MortgageTax (Vals AI)Not measured64.9%Only Qwen3.8 27B measured
MedCode (Vals AI)44.7%28.7%GPT-6 Luna
SimpleQA Verified41.4%Not measuredOnly GPT-6 Luna measured
LMArena Text: science13861467Qwen3.8 27B
LMArena Text: medicine and healthcare13521437Qwen3.8 27B
LMArena Text: legal and government14001447Qwen3.8 27B
LMArena Text: business and finance13881438Qwen3.8 27B
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index10
Web design benchmarks for GPT-6 Luna and Qwen3.8 27B
BenchmarkGPT-6 LunaQwen3.8 27BLeader
Design Arena: websites1272Not measuredOnly GPT-6 Luna measured
Design Arena: UI components1297Not measuredOnly GPT-6 Luna measured
Design Arena: game dev1259Not measuredOnly GPT-6 Luna measured
Design Arena: data viz1215Not measuredOnly GPT-6 Luna measured
Design Arena: 3D1217Not measuredOnly GPT-6 Luna measured
Design Arena: all code categories1271Not measuredOnly GPT-6 Luna measured
Design Arena: SVG1253Not measuredOnly GPT-6 Luna measured
Design Arena: ASCII art1156Not measuredOnly GPT-6 Luna measured
LiveBench design82.5%75.9%GPT-6 Luna
GeneralLike-for-likePublic boards, shown as published, kept out of the index325
General benchmarks for GPT-6 Luna and Qwen3.8 27B
BenchmarkGPT-6 LunaQwen3.8 27BLeader
Vals Index52.3%Not measuredOnly GPT-6 Luna measured
LiveBench data analysis73.4%76.6%Qwen3.8 27B
Public Benefits Bench (Vals AI)57.6%Not measuredOnly GPT-6 Luna measured
SAGE (Vals AI)48.1%52.4%Qwen3.8 27B
MedScribe (Vals AI)83.7%83.8%Qwen3.8 27B
Long context reasoning (AA-LCR)83.3%82.0%GPT-6 Luna
DTBench90.1%88.0%GPT-6 Luna
LMCA44.5%41.4%GPT-6 Luna
Surface Evolver BenchNot measured45.0%Only Qwen3.8 27B measured
Furniture assembly44.2%Not measuredOnly GPT-6 Luna measured
LMArena Text13891440Qwen3.8 27B
LMArena Text: instruction following14081436Qwen3.8 27B
LMArena Text: creative writing13631383Qwen3.8 27B
LMArena Vision12161269Qwen3.8 27B
LMArena Text: English13931448Qwen3.8 27B
LMArena Text: non-English13811428Qwen3.8 27B
LMArena Text: Chinese14271501Qwen3.8 27B
LMArena Text: German13761443Qwen3.8 27B
LMArena Text: Japanese13691387Qwen3.8 27B
LMArena Text: Korean13591384Qwen3.8 27B
LMArena Text: French14081465Qwen3.8 27B
LMArena Text: Spanish13911449Qwen3.8 27B
LMArena Text: Russian13921415Qwen3.8 27B
LMArena Text: Polish13831439Qwen3.8 27B
LMArena Text: multi-turn13921440Qwen3.8 27B
LMArena Text: longer queries14081448Qwen3.8 27B
LMArena Text: writing and language13841405Qwen3.8 27B
LMArena Text: entertainment and media13641393Qwen3.8 27B
LMArena Vision: English12041267Qwen3.8 27B
LMArena Vision: Chinese12661326Qwen3.8 27B
LMArena Vision: reading text12251281Qwen3.8 27B
LMArena Vision: humorNot measured1235Only Qwen3.8 27B measured
LMArena Vision: creative writing12051237Qwen3.8 27B
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-6 Luna and Qwen3.8 27B
BenchmarkGPT-6 LunaQwen3.8 27BLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

GPT-6 Luna$0.0003Fits in one request
Qwen3.8 27B$0.0007Fits in one request

GPT-6 Luna costs less

Repository review

50K input + 3K output tokens

GPT-6 Luna$0.0065Fits in one request
Qwen3.8 27B$0.0060Fits in one request

Qwen3.8 27B costs less

Agent loop

200K input + 10K output tokens

GPT-6 Luna$0.025Fits in one request
Qwen3.8 27B$0.021Fits in one request

Qwen3.8 27B costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of GPT-6 Luna and Qwen3.8 27B
SpecificationOpenAI GPT-6 LunaQwen3.8 27B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedSeptember 22, 2026August 14, 2026
Context window1.05M1M
Input $/Mtok$0.10$0.04
Output $/Mtok$0.50$1.35
Coding index71.473.6
Independent measurements behind it22
Cost per solved taskNot computable$1.26
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-6 Luna better than Qwen3.8 27B for coding?

Pick Qwen3.8 27B for coding: it scores 73.6 on the Vibe Coding Index against 71.4 for GPT-6 Luna. Pick GPT-6 Luna when output tokens cost 2.7x less, or when the context window is larger, 1.05M against 1M tokens.

Which is cheaper, GPT-6 Luna or Qwen3.8 27B?

GPT-6 Luna costs $0.10 per million input tokens and $0.50 per million output tokens; Qwen3.8 27B costs $0.04 and $1.35. Cost per solved task is known for Qwen3.8 27B only.

Which has the bigger context window, GPT-6 Luna or Qwen3.8 27B?

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

How many benchmarks is the GPT-6 Luna vs Qwen3.8 27B comparison based on?

71 benchmarks have a result for both models as of October 21, 2026. GPT-6 Luna's coding index rests on 2 independent benchmarks and Qwen3.8 27B's on 2. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gpt-6-luna-vs-qwen3-8-27b">LLMBenchmark.ai, GPT-6 Luna vs Qwen3.8 27B</a></p>