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GPT-5.6 Sol vs Qwen3.8 27B

Updated October 21, 2026. 84 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GPT-5.6 Sol Replace Qwen3.8 27B
GPT-5.6 SolOpenAI
Coding
76.7
Overall
47.0
Output $/M
$20.00
78
Qwen3.8 27BQwen
Coding
73.6
Overall
33.7
Output $/M
$1.35
6
vs boards won of 84 shared

Decision reading

Pick GPT-5.6 Sol for coding: it scores 76.7 on the Vibe Coding Index against 73.6 for Qwen3.8 27B.

Pick Qwen3.8 27B when output tokens cost 14.8x less, or when what matters is LiveCodeBench (Vals AI) or LiveBench research, where it leads.

Model AGPT-5.6 SolOpenAI76.7/1002 independent benchmarks$1.20 per solved taskModel BQwen3.8 27BQwen73.6/1002 independent benchmarks$1.26 per solved task
Shared results
84
GPT-5.6 Sol only
52
Qwen3.8 27B only
1
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-5.6 Sol 76.7 from 2 benchmarks, Qwen3.8 27B 73.6 from 2 benchmarks.
Widest category
Math, 25.5 points apart on average over 3 shared benchmarks.
Widest single gap
ProofBench: GPT-5.6 Sol 83.0% against Qwen3.8 27B 16.0%, 67.0 points apart on a 0 to 100 scale.
Output price
GPT-5.6 Sol $20.00 against Qwen3.8 27B $1.35 per million output tokens, 14.8x apart.
Context window
GPT-5.6 Sol 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-5.6 SolBarsQwen3.8 27BTies
Coding171
Intelligence20
Agentic work81
Reasoning120
Math30
Knowledge72
Web design10
General282
All shared boards786
CodingLike-for-likeFour of these boards feed the Vibe Coding Index171
Coding benchmarks for GPT-5.6 Sol and Qwen3.8 27B
BenchmarkGPT-5.6 SolQwen3.8 27BLeader
LiveBench coding89.7%86.8%GPT-5.6 Sol
LMArena WebDev16161593GPT-5.6 Sol
AA Coding Index77.468.1GPT-5.6 Sol
LiveCodeBench (Vals AI)82.6%84.0%Qwen3.8 27B
SWE-bench Verified (Vals AI)96.2%86.0%GPT-5.6 Sol
Terminal-Bench 4 (Vals AI)37.9%Not measuredOnly GPT-5.6 Sol measured
Vibe Code Bench (Vals AI)80.5%64.8%GPT-5.6 Sol
Code migration (Vals AI)52.9%14.2%GPT-5.6 Sol
ProgramBench (Vals AI)1.5%0.0%GPT-5.6 Sol
IOI (Vals AI)91.2%39.1%GPT-5.6 Sol
Terminal-Bench 2.1 (Vals AI)85.8%58.4%GPT-5.6 Sol
Vibe Code Bench 1-100 (Vals AI)20.0%Not measuredOnly GPT-5.6 Sol measured
SkillsBench (Vals AI)54.1%38.1%GPT-5.6 Sol
CyberBench (Vals AI)76.3%67.8%GPT-5.6 Sol
SciCode57.8%46.6%GPT-5.6 Sol
Terminal-Bench Hard (Artificial Analysis run)65.9%Not measuredOnly GPT-5.6 Sol measured
FrontierCode47.5%Not measuredOnly GPT-5.6 Sol measured
FrontierSWE32.2%Not measuredOnly GPT-5.6 Sol measured
GSO-Bench76.5%Not measuredOnly GPT-5.6 Sol measured
WeirdML88.8%Not measuredOnly GPT-5.6 Sol measured
MirrorCode20.0%Not measuredOnly GPT-5.6 Sol measured
ALE-Bench2176.9Not measuredOnly GPT-5.6 Sol measured
LMArena Text: coding14961483GPT-5.6 Sol
LMArena Text: software and IT14891478GPT-5.6 Sol
LMArena WebDev: React16201602GPT-5.6 Sol
LMArena WebDev: HTML16181570GPT-5.6 Sol
LMArena WebDev: from an image16091577GPT-5.6 Sol
Neither model has a result on the other 11 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for GPT-5.6 Sol and Qwen3.8 27B
BenchmarkGPT-5.6 SolQwen3.8 27BLeader
AA Intelligence Index47.033.7GPT-5.6 Sol
Epoch Capabilities Index162.8151.7GPT-5.6 Sol
Agentic workLike-for-likePublic boards, shown as published, kept out of the index81
Agentic work benchmarks for GPT-5.6 Sol and Qwen3.8 27B
BenchmarkGPT-5.6 SolQwen3.8 27BLeader
AA Agentic Index50.245.8GPT-5.6 Sol
Design Arena: agents building web apps1245Not measuredOnly GPT-5.6 Sol measured
Design Arena: agents building full-stack apps1261Not measuredOnly GPT-5.6 Sol measured
Design Arena: agents building mobile apps1249Not measuredOnly GPT-5.6 Sol measured
Design Arena: agents building Android apps1246Not measuredOnly GPT-5.6 Sol measured
Design Arena: agents building Godot games1260Not measuredOnly GPT-5.6 Sol measured
Design Arena: agents building games1267Not measuredOnly GPT-5.6 Sol measured
Design Arena: HTML slides1286Not measuredOnly GPT-5.6 Sol measured
Design Arena: PowerPoint slides1240Not measuredOnly GPT-5.6 Sol measured
LiveBench research54.5%59.4%Qwen3.8 27B
LiveBench browser88.0%32.0%GPT-5.6 Sol
LiveBench long agentic48.5%27.9%GPT-5.6 Sol
SREBench (Vals AI)30.5%Not measuredOnly GPT-5.6 Sol measured
Finance Agent (Vals AI)53.8%48.5%GPT-5.6 Sol
Tax Agent Bench (Vals AI)31.1%30.9%GPT-5.6 Sol
Legal Research Bench (Vals AI)48.1%36.1%GPT-5.6 Sol
Excel Modeling Benchmark (Vals AI)72.3%59.7%GPT-5.6 Sol
BioMysteryBench (Vals AI)71.1%Not measuredOnly GPT-5.6 Sol measured
Terminal-Bench-Science (Vals AI)20.0%0.0%GPT-5.6 Sol
Vals Science Index41.5%Not measuredOnly GPT-5.6 Sol measured
Time Horizon Index (Vals AI)23.8%Not measuredOnly GPT-5.6 Sol measured
CUA-bench (Vals AI)8.3%Not measuredOnly GPT-5.6 Sol measured
τ²-Bench Telecom85.1%Not measuredOnly GPT-5.6 Sol measured
APEX-AgentsNot measured47.5%Only Qwen3.8 27B measured
OSWorld 2.027.3%Not measuredOnly GPT-5.6 Sol measured
BALROG60.0%Not measuredOnly GPT-5.6 Sol measured
PostTrainBench36.2%Not measuredOnly GPT-5.6 Sol measured
Vending-Bench 2$9,619Not measuredOnly GPT-5.6 Sol measured
LMArena Search1261Not measuredOnly GPT-5.6 Sol measured
Neither model has a result on the other 10 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index120
Reasoning benchmarks for GPT-5.6 Sol and Qwen3.8 27B
BenchmarkGPT-5.6 SolQwen3.8 27BLeader
GPQA Diamond95.2%88.9%GPT-5.6 Sol
LiveBench reasoning91.7%80.0%GPT-5.6 Sol
MysteryMechanism (Vals AI)33.3%Not measuredOnly GPT-5.6 Sol measured
MMMU Pro (Vals AI)88.8%83.9%GPT-5.6 Sol
GPQA Diamond (Artificial Analysis run)94.1%90.5%GPT-5.6 Sol
Humanity's Last Exam (Artificial Analysis run)49.5%33.9%GPT-5.6 Sol
GPQA Diamond (Epoch AI run)93.5%Not measuredOnly GPT-5.6 Sol measured
ARC-AGI97.5%87.5%GPT-5.6 Sol
ARC-AGI-292.5%42.4%GPT-5.6 Sol
SimpleBench64.8%Not measuredOnly GPT-5.6 Sol measured
Chess puzzles59.0%Not measuredOnly GPT-5.6 Sol measured
Mystery game puzzles58.0%Not measuredOnly GPT-5.6 Sol measured
EBR-bench44.8%Not measuredOnly GPT-5.6 Sol measured
LMArena Text: hard prompts14831459GPT-5.6 Sol
LMArena Text: expert15171479GPT-5.6 Sol
LMArena Text: hard prompts in English14771461GPT-5.6 Sol
LMArena Vision: diagrams13051285GPT-5.6 Sol
LMArena Vision: homework13051295GPT-5.6 Sol
Neither model has a result on the other 3 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for GPT-5.6 Sol and Qwen3.8 27B
BenchmarkGPT-5.6 SolQwen3.8 27BLeader
OTIS Mock AIME100.0%Not measuredOnly GPT-5.6 Sol measured
FrontierMath, tiers 1 to 389.1%Not measuredOnly GPT-5.6 Sol measured
FrontierMath, tier 482.9%Not measuredOnly GPT-5.6 Sol measured
ProofBench83.0%16.0%GPT-5.6 Sol
LMArena Text: math14731455GPT-5.6 Sol
LMArena Text: mathematical work14961458GPT-5.6 Sol
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index72
Knowledge benchmarks for GPT-5.6 Sol and Qwen3.8 27B
BenchmarkGPT-5.6 SolQwen3.8 27BLeader
MMLU Pro89.1%84.3%GPT-5.6 Sol
LegalBench (Vals AI)87.0%82.4%GPT-5.6 Sol
CorpFin (Vals AI)64.4%Not measuredOnly GPT-5.6 Sol measured
TaxEval (Vals AI)74.8%70.8%GPT-5.6 Sol
MortgageTax (Vals AI)67.3%64.9%GPT-5.6 Sol
MedCode (Vals AI)44.0%28.7%GPT-5.6 Sol
SimpleQA Verified69.7%Not measuredOnly GPT-5.6 Sol measured
LMArena Text: science14551467Qwen3.8 27B
LMArena Text: medicine and healthcare14311437Qwen3.8 27B
LMArena Text: legal and government14761447GPT-5.6 Sol
LMArena Text: business and finance14571438GPT-5.6 Sol
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index10
Web design benchmarks for GPT-5.6 Sol and Qwen3.8 27B
BenchmarkGPT-5.6 SolQwen3.8 27BLeader
Design Arena: websites1321Not measuredOnly GPT-5.6 Sol measured
Design Arena: UI components1338Not measuredOnly GPT-5.6 Sol measured
Design Arena: game dev1368Not measuredOnly GPT-5.6 Sol measured
Design Arena: data viz1323Not measuredOnly GPT-5.6 Sol measured
Design Arena: 3D1385Not measuredOnly GPT-5.6 Sol measured
Design Arena: all code categories1341Not measuredOnly GPT-5.6 Sol measured
Design Arena: SVG1316Not measuredOnly GPT-5.6 Sol measured
Design Arena: ASCII art1302Not measuredOnly GPT-5.6 Sol measured
LiveBench design81.6%75.9%GPT-5.6 Sol
GeneralLike-for-likePublic boards, shown as published, kept out of the index282
General benchmarks for GPT-5.6 Sol and Qwen3.8 27B
BenchmarkGPT-5.6 SolQwen3.8 27BLeader
LiveBench data analysis79.8%76.6%GPT-5.6 Sol
Public Benefits Bench (Vals AI)66.5%Not measuredOnly GPT-5.6 Sol measured
SAGE (Vals AI)52.6%52.4%GPT-5.6 Sol
MedScribe (Vals AI)85.2%83.8%GPT-5.6 Sol
Vals Multimodal Index72.6%Not measuredOnly GPT-5.6 Sol measured
IFBench72.7%Not measuredOnly GPT-5.6 Sol measured
Long context reasoning (AA-LCR)84.0%82.0%GPT-5.6 Sol
DTBench95.7%88.0%GPT-5.6 Sol
LMCA58.5%41.4%GPT-5.6 Sol
Surface Evolver Bench93.1%45.0%GPT-5.6 Sol
Furniture assembly56.7%Not measuredOnly GPT-5.6 Sol measured
LMArena Text14571440GPT-5.6 Sol
LMArena Text: instruction following14831436GPT-5.6 Sol
LMArena Text: creative writing14491383GPT-5.6 Sol
LMArena Vision12811269GPT-5.6 Sol
LMArena Text: English14571448GPT-5.6 Sol
LMArena Text: non-English14511428GPT-5.6 Sol
LMArena Text: Chinese15251501GPT-5.6 Sol
LMArena Text: German14761443GPT-5.6 Sol
LMArena Text: Japanese14721387GPT-5.6 Sol
LMArena Text: Korean14421384GPT-5.6 Sol
LMArena Text: French14721465GPT-5.6 Sol
LMArena Text: Spanish14431449Qwen3.8 27B
LMArena Text: Russian14711415GPT-5.6 Sol
LMArena Text: Polish14591439GPT-5.6 Sol
LMArena Text: multi-turn14611440GPT-5.6 Sol
LMArena Text: longer queries14811448GPT-5.6 Sol
LMArena Text: writing and language14621405GPT-5.6 Sol
LMArena Text: entertainment and media14501393GPT-5.6 Sol
LMArena Vision: English12801267GPT-5.6 Sol
LMArena Vision: Chinese13131326Qwen3.8 27B
LMArena Vision: reading text12901281GPT-5.6 Sol
LMArena Vision: humor12461235GPT-5.6 Sol
LMArena Vision: creative writing12831237GPT-5.6 Sol
LMArena Document1483Not measuredOnly GPT-5.6 Sol measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-5.6 Sol and Qwen3.8 27B
BenchmarkGPT-5.6 SolQwen3.8 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-5.6 Sol$0.014Fits in one request
Qwen3.8 27B$0.0007Fits in one request

Qwen3.8 27B costs less

Repository review

50K input + 3K output tokens

GPT-5.6 Sol$0.260Fits in one request
Qwen3.8 27B$0.0060Fits in one request

Qwen3.8 27B costs less

Agent loop

200K input + 10K output tokens

GPT-5.6 Sol$1.00Fits 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-5.6 Sol and Qwen3.8 27B
SpecificationOpenAI GPT-5.6 SolQwen3.8 27B
MakerOpenAIQwen
WeightsNo public weights listedOpen weights
ReleasedJuly 9, 2026August 14, 2026
Context window1.05M1M
Input $/Mtok$4.00$0.04
Output $/Mtok$20.00$1.35
Coding index76.773.6
Independent measurements behind it22
Cost per solved task$1.20$1.26
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5.6 Sol better than Qwen3.8 27B for coding?

Pick GPT-5.6 Sol for coding: it scores 76.7 on the Vibe Coding Index against 73.6 for Qwen3.8 27B. Pick Qwen3.8 27B when output tokens cost 14.8x less, or when what matters is LiveCodeBench (Vals AI) or LiveBench research, where it leads.

Which is cheaper, GPT-5.6 Sol or Qwen3.8 27B?

GPT-5.6 Sol costs $4.00 per million input tokens and $20.00 per million output tokens; Qwen3.8 27B costs $0.04 and $1.35. Per solved SWE-bench Verified task, GPT-5.6 Sol costs $1.20 and Qwen3.8 27B $1.26.

Which has the bigger context window, GPT-5.6 Sol or Qwen3.8 27B?

GPT-5.6 Sol, with 1.05M tokens against 1M.

How many benchmarks is the GPT-5.6 Sol vs Qwen3.8 27B comparison based on?

84 benchmarks have a result for both models as of October 21, 2026. GPT-5.6 Sol'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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