Enter opens the highlighted result. Esc closes.

GPT-4 Turbo vs GPT-5.6 Sol

GPT-5.6 Sol leads GPT-4 Turbo on the Artificial Analysis Intelligence Index, 47.0 to 7.0, and GPT-5.6 Sol costs 1.5x less per output token ($20.00 vs $30.00 per million). Updated October 22, 2026; 38 benchmarks have a result for both.

GPT-4 TurboOpenAI
Coding
No data
Overall
No data
Output $/M
$30.00
0
GPT-5.6 SolOpenAI
Coding
73.5
Overall
74.7
Output $/M
$20.00
38
vs boards won of 38 shared

GPT-4 Turbo or GPT-5.6 Sol: which to pick

Only GPT-5.6 Sol has a coding score, 73.5 on the Vibe Coding Index; GPT-4 Turbo has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Shared results
38
GPT-4 Turbo only
4
GPT-5.6 Sol only
101
Like-for-like categories
6 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-4 Turbo not benchmarked, GPT-5.6 Sol 73.5 from 6 benchmarks.
Widest category
Coding, 43.6 points apart on average over 3 shared benchmarks.
Widest single gap
AA Coding Index: GPT-4 Turbo 21.5 against GPT-5.6 Sol 77.4, 55.9 points apart on a 0 to 100 scale.
Output price
GPT-4 Turbo $30.00 against GPT-5.6 Sol $20.00 per million output tokens, 1.5x apart.
Context window
GPT-4 Turbo takes 128K tokens, GPT-5.6 Sol 1.05M.

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-4 TurboBarsGPT-5.6 SolTies
Coding03
Intelligence02
Reasoning04
Math02
Knowledge05
General022
All shared boards038
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-4 Turbo and GPT-5.6 Sol
BenchmarkGPT-4 TurboGPT-5.6 SolLeader
LiveBench codingNot measured89.7%Only GPT-5.6 Sol measured
LMArena WebDevNot measured1616Only GPT-5.6 Sol measured
AA Coding Index21.577.4GPT-5.6 Sol
LiveCodeBench (Vals AI)Not measured82.6%Only GPT-5.6 Sol measured
SWE-bench Verified (Vals AI)Not measured96.2%Only GPT-5.6 Sol measured
Terminal-Bench 4 (Vals AI)Not measured37.9%Only GPT-5.6 Sol measured
Vibe Code Bench (Vals AI)Not measured80.5%Only GPT-5.6 Sol measured
Code migration (Vals AI)Not measured52.9%Only GPT-5.6 Sol measured
ProgramBench (Vals AI)Not measured1.5%Only GPT-5.6 Sol measured
IOI (Vals AI)Not measured91.2%Only GPT-5.6 Sol measured
Terminal-Bench 2.1 (Vals AI)Not measured85.8%Only GPT-5.6 Sol measured
Vibe Code Bench 1-100 (Vals AI)Not measured20.0%Only GPT-5.6 Sol measured
SkillsBench (Vals AI)Not measured54.1%Only GPT-5.6 Sol measured
CyberBench (Vals AI)Not measured76.3%Only GPT-5.6 Sol measured
LiveCodeBench (Artificial Analysis run)29.1%Not measuredOnly GPT-4 Turbo measured
SciCodeNot measured57.8%Only GPT-5.6 Sol measured
Terminal-Bench Hard (Artificial Analysis run)Not measured65.9%Only GPT-5.6 Sol measured
FrontierCodeNot measured47.5%Only GPT-5.6 Sol measured
FrontierSWENot measured32.2%Only GPT-5.6 Sol measured
GSO-BenchNot measured76.5%Only GPT-5.6 Sol measured
WeirdMLNot measured88.8%Only GPT-5.6 Sol measured
MirrorCodeNot measured20.0%Only GPT-5.6 Sol measured
ALE-BenchNot measured2176.9Only GPT-5.6 Sol measured
LMArena Text: coding12681496GPT-5.6 Sol
LMArena Text: software and IT12671489GPT-5.6 Sol
LMArena WebDev: ReactNot measured1620Only GPT-5.6 Sol measured
LMArena WebDev: HTMLNot measured1618Only GPT-5.6 Sol measured
LMArena WebDev: from an imageNot measured1609Only GPT-5.6 Sol measured
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-4 Turbo and GPT-5.6 Sol
BenchmarkGPT-4 TurboGPT-5.6 SolLeader
AA Intelligence Index7.047.0GPT-5.6 Sol
Epoch Capabilities Index127.3162.8GPT-5.6 Sol
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index28 boards, none shared
Agentic work benchmarks for GPT-4 Turbo and GPT-5.6 Sol
BenchmarkGPT-4 TurboGPT-5.6 SolLeader
AA Agentic IndexNot measured50.2Only GPT-5.6 Sol measured
Design Arena: agents building web appsNot measured1245Only GPT-5.6 Sol measured
Design Arena: agents building full-stack appsNot measured1261Only GPT-5.6 Sol measured
Design Arena: agents building mobile appsNot measured1248Only GPT-5.6 Sol measured
Design Arena: agents building Android appsNot measured1240Only GPT-5.6 Sol measured
Design Arena: agents building Godot gamesNot measured1260Only GPT-5.6 Sol measured
Design Arena: agents building gamesNot measured1266Only GPT-5.6 Sol measured
Design Arena: HTML slidesNot measured1236Only GPT-5.6 Sol measured
Design Arena: PowerPoint slidesNot measured1215Only GPT-5.6 Sol measured
LiveBench researchNot measured54.5%Only GPT-5.6 Sol measured
LiveBench browserNot measured88.0%Only GPT-5.6 Sol measured
LiveBench long agenticNot measured48.5%Only GPT-5.6 Sol measured
SREBench (Vals AI)Not measured30.5%Only GPT-5.6 Sol measured
Finance Agent (Vals AI)Not measured53.8%Only GPT-5.6 Sol measured
Tax Agent Bench (Vals AI)Not measured31.1%Only GPT-5.6 Sol measured
Legal Research Bench (Vals AI)Not measured48.1%Only GPT-5.6 Sol measured
Excel Modeling Benchmark (Vals AI)Not measured72.3%Only GPT-5.6 Sol measured
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)Not measured23.8%Only GPT-5.6 Sol measured
CUA-bench (Vals AI)Not measured8.3%Only GPT-5.6 Sol measured
τ²-Bench TelecomNot measured85.1%Only GPT-5.6 Sol measured
OSWorld 2.0Not measured27.3%Only GPT-5.6 Sol measured
BALROGNot measured60.0%Only GPT-5.6 Sol measured
PostTrainBenchNot measured36.2%Only GPT-5.6 Sol measured
Vending-Bench 2Not measured$9,619Only GPT-5.6 Sol measured
LMArena SearchNot measured1261Only GPT-5.6 Sol measured
Neither model has a result on the other 13 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for GPT-4 Turbo and GPT-5.6 Sol
BenchmarkGPT-4 TurboGPT-5.6 SolLeader
GPQA DiamondNot measured95.2%Only GPT-5.6 Sol measured
LiveBench reasoningNot measured91.7%Only GPT-5.6 Sol measured
MysteryMechanism (Vals AI)Not measured33.3%Only GPT-5.6 Sol measured
MMMU Pro (Vals AI)Not measured88.8%Only GPT-5.6 Sol measured
GPQA Diamond (Artificial Analysis run)Not measured94.1%Only GPT-5.6 Sol measured
Humanity's Last Exam (Artificial Analysis run)3.1%49.5%GPT-5.6 Sol
GPQA Diamond (Epoch AI run)Not measured93.5%Only GPT-5.6 Sol measured
ARC-AGINot measured97.5%Only GPT-5.6 Sol measured
ARC-AGI-2Not measured92.5%Only GPT-5.6 Sol measured
SimpleBenchNot measured64.8%Only GPT-5.6 Sol measured
Chess puzzlesNot measured59.0%Only GPT-5.6 Sol measured
Mystery game puzzlesNot measured58.0%Only GPT-5.6 Sol measured
EBR-benchNot measured44.8%Only GPT-5.6 Sol measured
LMArena Text: hard prompts12511483GPT-5.6 Sol
LMArena Text: expert12231517GPT-5.6 Sol
LMArena Text: hard prompts in English12661477GPT-5.6 Sol
LMArena Vision: diagramsNot measured1305Only GPT-5.6 Sol measured
LMArena Vision: homeworkNot measured1305Only GPT-5.6 Sol measured
Kagi LLM BenchmarkNot measured67.0%Only GPT-5.6 Sol measured
Neither model has a result on the other 3 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GPT-4 Turbo and GPT-5.6 Sol
BenchmarkGPT-4 TurboGPT-5.6 SolLeader
OTIS Mock AIMENot measured100.0%Only GPT-5.6 Sol measured
FrontierMath, tiers 1 to 3Not measured89.1%Only GPT-5.6 Sol measured
FrontierMath, tier 4Not measured82.9%Only GPT-5.6 Sol measured
ProofBenchNot measured83.0%Only GPT-5.6 Sol measured
LMArena Text: math12721473GPT-5.6 Sol
LMArena Text: mathematical work12681496GPT-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 index05
Knowledge benchmarks for GPT-4 Turbo and GPT-5.6 Sol
BenchmarkGPT-4 TurboGPT-5.6 SolLeader
MMLU ProNot measured89.1%Only GPT-5.6 Sol measured
LegalBench (Vals AI)80.5%87.0%GPT-5.6 Sol
CorpFin (Vals AI)Not measured64.4%Only GPT-5.6 Sol measured
TaxEval (Vals AI)Not measured74.8%Only GPT-5.6 Sol measured
MortgageTax (Vals AI)Not measured67.3%Only GPT-5.6 Sol measured
MedQA (Vals AI)82.0%Not measuredOnly GPT-4 Turbo measured
MedCode (Vals AI)Not measured44.0%Only GPT-5.6 Sol measured
MMLU Pro (Artificial Analysis run)69.4%Not measuredOnly GPT-4 Turbo measured
SimpleQA VerifiedNot measured69.7%Only GPT-5.6 Sol measured
MMLU81.3%Not measuredOnly GPT-4 Turbo measured
LMArena Text: science12561455GPT-5.6 Sol
LMArena Text: medicine and healthcare12391431GPT-5.6 Sol
LMArena Text: legal and government12651476GPT-5.6 Sol
LMArena Text: business and finance12221457GPT-5.6 Sol
FACTS Benchmark SuiteNot measured52.4%Only GPT-5.6 Sol measured
Neither model has a result on the other 3 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for GPT-4 Turbo and GPT-5.6 Sol
BenchmarkGPT-4 TurboGPT-5.6 SolLeader
Design Arena: websitesNot measured1321Only GPT-5.6 Sol measured
Design Arena: UI componentsNot measured1335Only GPT-5.6 Sol measured
Design Arena: game devNot measured1367Only GPT-5.6 Sol measured
Design Arena: data vizNot measured1322Only GPT-5.6 Sol measured
Design Arena: 3DNot measured1384Only GPT-5.6 Sol measured
Design Arena: all code categoriesNot measured1341Only GPT-5.6 Sol measured
Design Arena: SVGNot measured1314Only GPT-5.6 Sol measured
Design Arena: ASCII artNot measured1304Only GPT-5.6 Sol measured
LiveBench designNot measured81.6%Only GPT-5.6 Sol measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index022
General benchmarks for GPT-4 Turbo and GPT-5.6 Sol
BenchmarkGPT-4 TurboGPT-5.6 SolLeader
LiveBench data analysisNot measured79.8%Only GPT-5.6 Sol measured
Public Benefits Bench (Vals AI)Not measured66.5%Only GPT-5.6 Sol measured
SAGE (Vals AI)Not measured52.6%Only GPT-5.6 Sol measured
MedScribe (Vals AI)Not measured85.2%Only GPT-5.6 Sol measured
Vals Multimodal IndexNot measured72.6%Only GPT-5.6 Sol measured
IFBenchNot measured72.7%Only GPT-5.6 Sol measured
Long context reasoning (AA-LCR)Not measured84.0%Only GPT-5.6 Sol measured
DTBench61.6%95.7%GPT-5.6 Sol
LMCA9.8%58.5%GPT-5.6 Sol
Surface Evolver BenchNot measured93.1%Only GPT-5.6 Sol measured
Furniture assemblyNot measured56.7%Only GPT-5.6 Sol measured
LMArena Text12721457GPT-5.6 Sol
LMArena Text: instruction following12491483GPT-5.6 Sol
LMArena Text: creative writing12681449GPT-5.6 Sol
LMArena Vision10901281GPT-5.6 Sol
LMArena Text: English12911457GPT-5.6 Sol
LMArena Text: non-English12451451GPT-5.6 Sol
LMArena Text: Chinese12421525GPT-5.6 Sol
LMArena Text: German12591476GPT-5.6 Sol
LMArena Text: Japanese11941472GPT-5.6 Sol
LMArena Text: Korean11871442GPT-5.6 Sol
LMArena Text: French12761472GPT-5.6 Sol
LMArena Text: Spanish12601443GPT-5.6 Sol
LMArena Text: Russian12591471GPT-5.6 Sol
LMArena Text: Polish13021459GPT-5.6 Sol
LMArena Text: multi-turn12671461GPT-5.6 Sol
LMArena Text: longer queries12541481GPT-5.6 Sol
LMArena Text: writing and language12791462GPT-5.6 Sol
LMArena Text: entertainment and media12581450GPT-5.6 Sol
LMArena Vision: English10971280GPT-5.6 Sol
LMArena Vision: Chinese10451313GPT-5.6 Sol
LMArena Vision: reading textNot measured1290Only GPT-5.6 Sol measured
LMArena Vision: humorNot measured1246Only GPT-5.6 Sol measured
LMArena Vision: creative writingNot measured1283Only GPT-5.6 Sol measured
LMArena DocumentNot measured1483Only 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-4 Turbo and GPT-5.6 Sol
BenchmarkGPT-4 TurboGPT-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-4 Turbo$0.025Fits 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-4 Turbo$0.590Fits 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-4 Turbo$2.30Exceeds the context window
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-4 Turbo and GPT-5.6 Sol
SpecificationOpenAI GPT-4 TurboOpenAI GPT-5.6 Sol
MakerOpenAIOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedApril 9, 2024July 9, 2026
Context window128K1.05M
Input $/Mtok$10.00$4.00
Output $/Mtok$30.00$20.00
Coding indexNot benchmarked73.5
Independent measurements behind it06
Cost per solved taskNot computable$1.20
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4 Turbo better than GPT-5.6 Sol for coding?

Only GPT-5.6 Sol has a coding score, 73.5 on the Vibe Coding Index; GPT-4 Turbo has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, GPT-4 Turbo or GPT-5.6 Sol?

GPT-4 Turbo costs $10.00 per million input tokens and $30.00 per million output tokens; GPT-5.6 Sol costs $4.00 and $20.00. Cost per solved task is known for GPT-5.6 Sol only.

Which has the bigger context window, GPT-4 Turbo or GPT-5.6 Sol?

GPT-5.6 Sol, with 1.05M tokens against 128K.

How many benchmarks is the GPT-4 Turbo vs GPT-5.6 Sol comparison based on?

38 benchmarks have a result for both models as of October 22, 2026. GPT-4 Turbo's coding index rests on 0 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.

Compare next