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GPT-5.5 vs GPT-5.6 Sol

GPT-5.6 Sol leads GPT-5.5 on coding, 73.5 to 71.3 on the Vibe Coding Index, and GPT-5.6 Sol costs 1.5x less per output token ($20.00 vs $30.00 per million). Updated October 22, 2026; 126 benchmarks have a result for both.

GPT-5.5OpenAI
Coding
71.3
Overall
69.2
Output $/M
$30.00
49
GPT-5.6 SolOpenAI
Coding
73.5
Overall
74.7
Output $/M
$20.00
77
vs boards won of 126 shared

GPT-5.5 or GPT-5.6 Sol: which to pick

Pick GPT-5.6 Sol for coding: it scores 73.5 on the Vibe Coding Index against 71.3 for GPT-5.5.

Pick GPT-5.5 for work measured by LiveCodeBench (Vals AI) or SkillsBench (Vals AI), where it leads.

Shared results
126
GPT-5.5 only
8
GPT-5.6 Sol only
13
Like-for-like categories
8 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

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-5.5 71.3 from 5 benchmarks, GPT-5.6 Sol 73.5 from 6 benchmarks.
Widest category
Agentic work, 13.9 points apart on average over 22 shared benchmarks.
Widest single gap
LiveBench browser: GPT-5.5 48.0% against GPT-5.6 Sol 88.0%, 40.0 points apart on a 0 to 100 scale.
Output price
GPT-5.5 $30.00 against GPT-5.6 Sol $20.00 per million output tokens, 1.5x apart.
Context window
Both take 1.05M tokens.

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-5.5BarsGPT-5.6 SolTies
Coding319
Intelligence02
Agentic work220
Reasoning711
Math15
Knowledge93
Web design09
General278
All shared boards4977
CodingLike-for-likeSix of these boards feed the Vibe Coding Index319
Coding benchmarks for GPT-5.5 and GPT-5.6 Sol
BenchmarkGPT-5.5GPT-5.6 SolLeader
LiveBench coding85.1%89.7%GPT-5.6 Sol
LMArena WebDev15131616GPT-5.6 Sol
AA Coding Index74.977.4GPT-5.6 Sol
LiveCodeBench (Vals AI)85.3%82.6%GPT-5.5
SWE-bench Verified (Vals AI)82.6%96.2%GPT-5.6 Sol
Terminal-Bench 4 (Vals AI)Not measured37.9%Only GPT-5.6 Sol measured
Vibe Code Bench (Vals AI)69.8%80.5%GPT-5.6 Sol
Code migration (Vals AI)45.2%52.9%GPT-5.6 Sol
ProgramBench (Vals AI)0.5%1.5%GPT-5.6 Sol
IOI (Vals AI)Not measured91.2%Only GPT-5.6 Sol measured
Terminal-Bench 2.1 (Vals AI)76.4%85.8%GPT-5.6 Sol
Vibe Code Bench 1-100 (Vals AI)Not measured20.0%Only GPT-5.6 Sol measured
SkillsBench (Vals AI)62.5%54.1%GPT-5.5
CyberBench (Vals AI)Not measured76.3%Only GPT-5.6 Sol measured
SciCode56.1%57.8%GPT-5.6 Sol
Terminal-Bench Hard (Artificial Analysis run)60.6%65.9%GPT-5.6 Sol
Terminal-Bench84.7%Not measuredOnly GPT-5.5 measured
FrontierCode43.0%47.5%GPT-5.6 Sol
FrontierSWENot measured32.2%Only GPT-5.6 Sol measured
GSO-Bench40.2%76.5%GPT-5.6 Sol
WeirdML84.9%88.8%GPT-5.6 Sol
MirrorCode10.0%20.0%GPT-5.6 Sol
ALE-Bench1943.02176.9GPT-5.6 Sol
LMArena Text: coding14941496GPT-5.6 Sol
LMArena Text: software and IT14931489GPT-5.5
LMArena WebDev: React15061620GPT-5.6 Sol
LMArena WebDev: HTML15431618GPT-5.6 Sol
LMArena WebDev: from an image15321609GPT-5.6 Sol
SciCodeNot measured10.8%Only GPT-5.6 Sol measured
Neither model has a result on the other 10 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-5.5 and GPT-5.6 Sol
BenchmarkGPT-5.5GPT-5.6 SolLeader
AA Intelligence Index38.447.0GPT-5.6 Sol
Epoch Capabilities Index159.7162.8GPT-5.6 Sol
Agentic workLike-for-likePublic boards, shown as published, kept out of the index220
Agentic work benchmarks for GPT-5.5 and GPT-5.6 Sol
BenchmarkGPT-5.5GPT-5.6 SolLeader
AA Agentic Index36.450.2GPT-5.6 Sol
Design Arena: agents building web apps11171245GPT-5.6 Sol
Design Arena: agents building full-stack apps10891261GPT-5.6 Sol
Design Arena: agents building mobile apps11421248GPT-5.6 Sol
Design Arena: agents building Android apps11641240GPT-5.6 Sol
Design Arena: agents building Godot games11731260GPT-5.6 Sol
Design Arena: agents building games11791266GPT-5.6 Sol
Design Arena: HTML slides10171236GPT-5.6 Sol
Design Arena: PowerPoint slides10841215GPT-5.6 Sol
LiveBench research61.6%54.5%GPT-5.5
LiveBench browser48.0%88.0%GPT-5.6 Sol
LiveBench long agentic44.6%48.5%GPT-5.6 Sol
SREBench (Vals AI)3.8%30.5%GPT-5.6 Sol
Finance Agent (Vals AI)51.8%53.8%GPT-5.6 Sol
Tax Agent Bench (Vals AI)21.8%31.1%GPT-5.6 Sol
Legal Research Bench (Vals AI)40.4%48.1%GPT-5.6 Sol
Excel Modeling Benchmark (Vals AI)64.5%72.3%GPT-5.6 Sol
BioMysteryBench (Vals AI)Not measured71.1%Only GPT-5.6 Sol measured
Terminal-Bench-Science (Vals AI)Not measured20.0%Only GPT-5.6 Sol measured
Vals Science IndexNot measured41.5%Only GPT-5.6 Sol measured
Time Horizon Index (Vals AI)8.3%23.8%GPT-5.6 Sol
CUA-bench (Vals AI)Not measured8.3%Only GPT-5.6 Sol measured
τ²-Bench Telecom93.9%85.1%GPT-5.5
APEX-Agents55.1%Not measuredOnly GPT-5.5 measured
Remote Labor Index6.3%Not measuredOnly GPT-5.5 measured
OSWorld 2.013.0%27.3%GPT-5.6 Sol
BALROGNot measured60.0%Only GPT-5.6 Sol measured
DeepResearch Bench54.0%Not measuredOnly GPT-5.5 measured
PostTrainBench27.2%36.2%GPT-5.6 Sol
Vending-Bench 2$7,524$9,619GPT-5.6 Sol
LMArena SearchNot measured1261Only 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 index711
Reasoning benchmarks for GPT-5.5 and GPT-5.6 Sol
BenchmarkGPT-5.5GPT-5.6 SolLeader
GPQA Diamond93.2%95.2%GPT-5.6 Sol
LiveBench reasoning89.7%91.7%GPT-5.6 Sol
MysteryMechanism (Vals AI)Not measured33.3%Only GPT-5.6 Sol measured
MMMU Pro (Vals AI)88.3%88.8%GPT-5.6 Sol
GPQA Diamond (Artificial Analysis run)93.5%94.1%GPT-5.6 Sol
Humanity's Last Exam (Artificial Analysis run)45.8%49.5%GPT-5.6 Sol
GPQA Diamond (Epoch AI run)90.7%93.5%GPT-5.6 Sol
ARC-AGI95.0%97.5%GPT-5.6 Sol
ARC-AGI-285.0%92.5%GPT-5.6 Sol
SimpleBench69.0%64.8%GPT-5.5
Chess puzzles63.0%59.0%GPT-5.5
Mystery game puzzles56.0%58.0%GPT-5.6 Sol
EBR-bench34.3%44.8%GPT-5.6 Sol
LMArena Text: hard prompts14891483GPT-5.5
LMArena Text: expert15071517GPT-5.6 Sol
LMArena Text: hard prompts in English14831477GPT-5.5
LMArena Vision: diagrams13251305GPT-5.5
LMArena Vision: homework13321305GPT-5.5
Kagi LLM Benchmark88.8%67.0%GPT-5.5
Neither model has a result on the other 3 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index15
Math benchmarks for GPT-5.5 and GPT-5.6 Sol
BenchmarkGPT-5.5GPT-5.6 SolLeader
OTIS Mock AIME84.4%100.0%GPT-5.6 Sol
FrontierMath, tiers 1 to 385.3%89.1%GPT-5.6 Sol
FrontierMath, tier 472.5%82.9%GPT-5.6 Sol
ProofBench50.0%83.0%GPT-5.6 Sol
LMArena Text: math14871473GPT-5.5
LMArena Text: mathematical work14961496GPT-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 index93
Knowledge benchmarks for GPT-5.5 and GPT-5.6 Sol
BenchmarkGPT-5.5GPT-5.6 SolLeader
MMLU Pro88.1%89.1%GPT-5.6 Sol
LegalBench (Vals AI)86.5%87.0%GPT-5.6 Sol
CaseLaw (Vals AI)66.2%Not measuredOnly GPT-5.5 measured
CorpFin (Vals AI)68.4%64.4%GPT-5.5
TaxEval (Vals AI)75.0%74.8%GPT-5.5
MortgageTax (Vals AI)68.8%67.3%GPT-5.5
MedCode (Vals AI)49.1%44.0%GPT-5.5
SimpleQA Verified63.0%69.7%GPT-5.6 Sol
LMArena Text: science14851455GPT-5.5
LMArena Text: medicine and healthcare14651431GPT-5.5
LMArena Text: legal and government14911476GPT-5.5
LMArena Text: business and finance14781457GPT-5.5
FACTS Benchmark Suite66.7%52.4%GPT-5.5
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index09
Web design benchmarks for GPT-5.5 and GPT-5.6 Sol
BenchmarkGPT-5.5GPT-5.6 SolLeader
Design Arena: websites12561321GPT-5.6 Sol
Design Arena: UI components12571335GPT-5.6 Sol
Design Arena: game dev12931367GPT-5.6 Sol
Design Arena: data viz12641322GPT-5.6 Sol
Design Arena: 3D11971384GPT-5.6 Sol
Design Arena: all code categories12601341GPT-5.6 Sol
Design Arena: SVG12341314GPT-5.6 Sol
Design Arena: ASCII art12551304GPT-5.6 Sol
LiveBench design70.3%81.6%GPT-5.6 Sol
GeneralLike-for-likePublic boards, shown as published, kept out of the index278
General benchmarks for GPT-5.5 and GPT-5.6 Sol
BenchmarkGPT-5.5GPT-5.6 SolLeader
LiveBench data analysis81.6%79.8%GPT-5.5
Public Benefits Bench (Vals AI)60.9%66.5%GPT-5.6 Sol
SAGE (Vals AI)51.5%52.6%GPT-5.6 Sol
MedScribe (Vals AI)86.9%85.2%GPT-5.5
Vals Multimodal Index68.1%72.6%GPT-5.6 Sol
IFBench75.9%72.7%GPT-5.5
Long context reasoning (AA-LCR)84.3%84.0%GPT-5.5
DTBench96.0%95.7%GPT-5.5
LMCA54.3%58.5%GPT-5.6 Sol
Surface Evolver Bench88.1%93.1%GPT-5.6 Sol
Furniture assembly44.2%56.7%GPT-5.6 Sol
ExploitBench47.4%Not measuredOnly GPT-5.5 measured
CL-bench Life22.2%Not measuredOnly GPT-5.5 measured
LMArena Text14711457GPT-5.5
LMArena Text: instruction following14781483GPT-5.6 Sol
LMArena Text: creative writing14551449GPT-5.5
LMArena Vision12971281GPT-5.5
LMArena Text: English14701457GPT-5.5
LMArena Text: non-English14671451GPT-5.5
LMArena Text: Chinese15341525GPT-5.5
LMArena Text: German14801476GPT-5.5
LMArena Text: Japanese14991472GPT-5.5
LMArena Text: Korean14601442GPT-5.5
LMArena Text: French14851472GPT-5.5
LMArena Text: Spanish14681443GPT-5.5
LMArena Text: Russian14731471GPT-5.5
LMArena Text: Polish14651459GPT-5.5
LMArena Text: multi-turn14761461GPT-5.5
LMArena Text: longer queries14841481GPT-5.5
LMArena Text: writing and language14661462GPT-5.5
LMArena Text: entertainment and media14491450GPT-5.6 Sol
LMArena Vision: English12921280GPT-5.5
LMArena Vision: Chinese13601313GPT-5.5
LMArena Vision: reading text13061290GPT-5.5
LMArena Vision: humor12931246GPT-5.5
LMArena Vision: recognizing things1231Not measuredOnly GPT-5.5 measured
LMArena Vision: creative writing13011283GPT-5.5
LMArena Document14861483GPT-5.5
Neither model has a result on the other 8 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-5.5 and GPT-5.6 Sol
BenchmarkGPT-5.5GPT-5.6 SolLeader
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-5.5$0.020Fits in one request
GPT-5.6 Sol$0.014Fits in one request

GPT-5.6 Sol costs less

Repository review

50K input + 3K output tokens

GPT-5.5$0.340Fits in one request
GPT-5.6 Sol$0.260Fits in one request

GPT-5.6 Sol costs less

Agent loop

200K input + 10K output tokens

GPT-5.5$1.30Fits in one request
GPT-5.6 Sol$1.00Fits in one request

GPT-5.6 Sol 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-5.5 and GPT-5.6 Sol
SpecificationOpenAI GPT-5.5OpenAI GPT-5.6 Sol
MakerOpenAIOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedApril 24, 2026July 9, 2026
Context window1.05M1.05M
Input $/Mtok$5.00$4.00
Output $/Mtok$30.00$20.00
Coding index71.373.5
Independent measurements behind it56
Cost per solved task$1.65$1.20
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5.5 better than GPT-5.6 Sol for coding?

Pick GPT-5.6 Sol for coding: it scores 73.5 on the Vibe Coding Index against 71.3 for GPT-5.5. Pick GPT-5.5 for work measured by LiveCodeBench (Vals AI) or SkillsBench (Vals AI), where it leads.

Which is cheaper, GPT-5.5 or GPT-5.6 Sol?

GPT-5.5 costs $5.00 per million input tokens and $30.00 per million output tokens; GPT-5.6 Sol costs $4.00 and $20.00. Per solved SWE-bench Verified task, GPT-5.5 costs $1.65 and GPT-5.6 Sol $1.20.

Which has the bigger context window, GPT-5.5 or GPT-5.6 Sol?

Neither: both take 1.05M tokens.

How many benchmarks is the GPT-5.5 vs GPT-5.6 Sol comparison based on?

126 benchmarks have a result for both models as of October 22, 2026. GPT-5.5's coding index rests on 5 independent benchmarks and GPT-5.6 Sol's on 6. Where only one model has a result, the page says so instead of naming a winner.

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