GPT-5.6 Sol vs Kimi K3.1 Pro
Kimi K3.1 Pro leads GPT-5.6 Sol on coding, 82.2 to 70.7 on the Vibe Coding Index, and Kimi K3.1 Pro costs 2.0x less per output token ($10.00 vs $20.00 per million). Updated October 29, 2026; 25 benchmarks have a result for both.
vs boards won of 25 shared
GPT-5.6 Sol or Kimi K3.1 Pro: which to pick
Pick Kimi K3.1 Pro for coding: it scores 82.2 on the Vibe Coding Index against 70.7 for GPT-5.6 Sol, though on 4 benchmarks against 5.
Pick GPT-5.6 Sol for a larger context window (1.05M against 1.05M tokens) and work measured by IOI (Vals AI) or ALE-Bench, where it leads.
Model AGPT-5.6 SolOpenAI70.7/1005 independent benchmarks$1.20 per solved taskModel BKimi K3.1 ProMoonshot AI82.2/1004 independent benchmarksNo cost per solved task
- Shared results
- 25
- GPT-5.6 Sol only
- 114
- Kimi K3.1 Pro only
- 10
- 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.
Coding
Vibe Coding Index, six public coding benchmarks
Kimi K3.1 Pro
Kimi K3.1 Pro scores 82.2 against 70.7.
5 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only Kimi K3.1 Pro has a AA Intelligence Index result, 46.0.
Directional only
Agentic work
AA Agentic Index
No call
Only GPT-5.6 Sol has a AA Agentic Index result, 47.4.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.6 Sol has a GPQA Diamond result, 95.2%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.6 Sol has a MMLU Pro result, 89.1%.
Directional only
Web design
Design Arena: websites
Kimi K3.1 Pro
Kimi K3.1 Pro leads, 1325 against 1320.
Same board, both measured
General
Vals Index
No call
Only Kimi K3.1 Pro has a Vals Index result, 62.5%.
Directional only
Long documents
Listed context window
GPT-5.6 Sol
GPT-5.6 Sol takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K3.1 Pro
GPT-5.6 Sol $0.014, Kimi K3.1 Pro $0.0070 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.6 Sol has the number, $1.20.
Directional only
At a glance
- Coding index
- GPT-5.6 Sol 70.7 from 5 benchmarks, Kimi K3.1 Pro 82.2 from 4 benchmarks.
- Widest category
- Coding, 8.8 points apart on average over 8 shared benchmarks.
- Widest single gap
- Terminal-Bench 4 (Vals AI): GPT-5.6 Sol 37.9% against Kimi K3.1 Pro 63.6%, 34.3 points apart on a 0 to 100 scale.
- Output price
- GPT-5.6 Sol $20.00 against Kimi K3.1 Pro $10.00 per million output tokens, 2.0x apart.
- Context window
- GPT-5.6 Sol takes 1.05M tokens, Kimi K3.1 Pro 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.
| Category | GPT-5.6 Sol | Bars | Kimi K3.1 Pro | Ties |
|---|---|---|---|---|
| Coding | 2 | 6 | ||
| Agentic work | 2 | 3 | ||
| Reasoning | 1 | 1 | ||
| Math | 1 | 1 | ||
| Web design | 1 | 6 | ||
| General | 0 | 1 | ||
| All shared boards | 7 | 18 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index26
| Benchmark | GPT-5.6 Sol | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 81.8% | Only Kimi K3.1 Pro measured |
| LMArena WebDev | 1616 | 1695 | Kimi K3.1 Pro |
| AA Coding Index | 78.3 | Not measured | Only GPT-5.6 Sol measured |
| LiveCodeBench (Vals AI) | 82.6% | Not measured | Only GPT-5.6 Sol measured |
| SWE-bench Verified (Vals AI) | 96.2% | Not measured | Only GPT-5.6 Sol measured |
| Terminal-Bench 4 (Vals AI) | 37.9% | 63.6% | Kimi K3.1 Pro |
| Vibe Code Bench (Vals AI) | 80.5% | 84.9% | Kimi K3.1 Pro |
| Code migration (Vals AI) | 52.9% | Not measured | Only GPT-5.6 Sol measured |
| ProgramBench (Vals AI) | 1.5% | Not measured | Only GPT-5.6 Sol measured |
| IOI (Vals AI) | 91.2% | 81.9% | GPT-5.6 Sol |
| Terminal-Bench 2.1 (Vals AI) | 85.8% | Not measured | Only GPT-5.6 Sol measured |
| Vibe Code Bench 1-100 (Vals AI) | 20.0% | Not measured | Only GPT-5.6 Sol measured |
| SkillsBench (Vals AI) | 54.1% | Not measured | Only GPT-5.6 Sol measured |
| CyberBench (Vals AI) | 76.3% | Not measured | Only GPT-5.6 Sol measured |
| SciCode | 57.8% | 60.8% | Kimi K3.1 Pro |
| Terminal-Bench Hard (Artificial Analysis run) | 65.9% | Not measured | Only GPT-5.6 Sol measured |
| FrontierCode | 47.5% | Not measured | Only GPT-5.6 Sol measured |
| FrontierSWE | 32.2% | Not measured | Only GPT-5.6 Sol measured |
| GSO-Bench | 76.5% | Not measured | Only GPT-5.6 Sol measured |
| WeirdML | 88.8% | Not measured | Only GPT-5.6 Sol measured |
| MirrorCode | 20.0% | Not measured | Only GPT-5.6 Sol measured |
| ALE-Bench | 2176.9 | 1932.8 | GPT-5.6 Sol |
| LMArena Text: coding | 1495 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: software and IT | 1488 | Not measured | Only GPT-5.6 Sol measured |
| LMArena WebDev: React | 1618 | 1701 | Kimi K3.1 Pro |
| LMArena WebDev: HTML | 1617 | 1706 | Kimi K3.1 Pro |
| LMArena WebDev: from an image | 1609 | Not measured | Only GPT-5.6 Sol measured |
| SciCode | 10.8% | Not measured | Only GPT-5.6 Sol measured |
| SWE-Bench Pro V2 | 95.5% | Not measured | Only GPT-5.6 Sol measured |
| SWE Atlas: Codebase QnA | 46.0% | Not measured | Only GPT-5.6 Sol measured |
| SWE Atlas: Test Writing | 45.9% | Not measured | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 12 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.6 Sol | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 46.0 | Only Kimi K3.1 Pro measured |
| Epoch Capabilities Index | 162.8 | Not measured | Only GPT-5.6 Sol measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index23
| Benchmark | GPT-5.6 Sol | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| AA Agentic Index | 47.4 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: agents building web apps | 1245 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: agents building full-stack apps | 1262 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: agents building mobile apps | 1241 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: agents building Android apps | 1234 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: agents building Godot games | 1260 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: agents building games | 1231 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: HTML slides | 1182 | Not measured | Only GPT-5.6 Sol measured |
| Design Arena: PowerPoint slides | 1195 | Not measured | Only GPT-5.6 Sol measured |
| LiveBench research | Not measured | 77.9% | Only Kimi K3.1 Pro measured |
| LiveBench browser | Not measured | 75.9% | Only Kimi K3.1 Pro measured |
| LiveBench long agentic | Not measured | 39.1% | Only Kimi K3.1 Pro measured |
| SREBench (Vals AI) | 30.5% | Not measured | Only GPT-5.6 Sol measured |
| Finance Agent (Vals AI) | 53.8% | Not measured | Only GPT-5.6 Sol measured |
| Tax Agent Bench (Vals AI) | 31.1% | 24.9% | GPT-5.6 Sol |
| Legal Research Bench (Vals AI) | 48.1% | 37.5% | GPT-5.6 Sol |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 11.7% | Only Kimi K3.1 Pro measured |
| Excel Modeling Benchmark (Vals AI) | 72.3% | Not measured | Only GPT-5.6 Sol measured |
| BioMysteryBench (Vals AI) | 71.1% | 75.6% | Kimi K3.1 Pro |
| Terminal-Bench-Science (Vals AI) | 20.0% | 31.4% | Kimi K3.1 Pro |
| Vals Science Index | 41.5% | 44.4% | Kimi K3.1 Pro |
| Time Horizon Index (Vals AI) | 23.8% | Not measured | Only GPT-5.6 Sol measured |
| CUA-bench (Vals AI) | 8.3% | Not measured | Only GPT-5.6 Sol measured |
| τ²-Bench Telecom | 85.1% | Not measured | Only GPT-5.6 Sol measured |
| OSWorld 2.0 | 27.3% | Not measured | Only GPT-5.6 Sol measured |
| BALROG | 60.0% | Not measured | Only GPT-5.6 Sol measured |
| PostTrainBench | 36.2% | Not measured | Only GPT-5.6 Sol measured |
| Vending-Bench 2 | $9,619 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Search | 1261 | Not measured | Only GPT-5.6 Sol measured |
| MCP Atlas | 81.8% | Not measured | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 12 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GPT-5.6 Sol | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 95.2% | Not measured | Only GPT-5.6 Sol measured |
| LiveBench reasoning | Not measured | 91.1% | Only Kimi K3.1 Pro measured |
| MysteryMechanism (Vals AI) | 33.3% | 26.1% | GPT-5.6 Sol |
| MMMU Pro (Vals AI) | 88.8% | Not measured | Only GPT-5.6 Sol measured |
| GPQA Diamond (Artificial Analysis run) | 94.1% | Not measured | Only GPT-5.6 Sol measured |
| Humanity's Last Exam (Artificial Analysis run) | 49.5% | 52.5% | Kimi K3.1 Pro |
| GPQA Diamond (Epoch AI run) | 93.5% | Not measured | Only GPT-5.6 Sol measured |
| ARC-AGI | 97.5% | Not measured | Only GPT-5.6 Sol measured |
| ARC-AGI-2 | 92.5% | Not measured | Only GPT-5.6 Sol measured |
| SimpleBench | 64.8% | Not measured | Only GPT-5.6 Sol measured |
| Chess puzzles | 59.0% | Not measured | Only GPT-5.6 Sol measured |
| Mystery game puzzles | 58.0% | Not measured | Only GPT-5.6 Sol measured |
| EBR-bench | 44.8% | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: hard prompts | 1483 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: expert | 1516 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: hard prompts in English | 1477 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Vision: diagrams | 1305 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Vision: homework | 1305 | Not measured | Only GPT-5.6 Sol measured |
| Kagi LLM Benchmark | 67.0% | Not measured | Only GPT-5.6 Sol measured |
| Humanity's Last Exam (Scale run) | 31.2% | Not measured | 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 index11
| Benchmark | GPT-5.6 Sol | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | Not measured | Only GPT-5.6 Sol measured |
| FrontierMath, tiers 1 to 3 | 89.1% | Not measured | Only GPT-5.6 Sol measured |
| FrontierMath, tier 4 | 82.9% | Not measured | Only GPT-5.6 Sol measured |
| ProofBench | 83.0% | 91.0% | Kimi K3.1 Pro |
| LMArena Text: math | 1472 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: mathematical work | 1494 | Not measured | Only GPT-5.6 Sol measured |
| MathArena | 61.3% | 59.6% | GPT-5.6 Sol |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
| Benchmark | GPT-5.6 Sol | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| MMLU Pro | 89.1% | Not measured | Only GPT-5.6 Sol measured |
| LegalBench (Vals AI) | 87.0% | Not measured | Only GPT-5.6 Sol measured |
| CorpFin (Vals AI) | 64.4% | Not measured | Only GPT-5.6 Sol measured |
| TaxEval (Vals AI) | 74.8% | Not measured | Only GPT-5.6 Sol measured |
| MortgageTax (Vals AI) | 67.3% | Not measured | Only GPT-5.6 Sol measured |
| MedCode (Vals AI) | 44.0% | Not measured | Only GPT-5.6 Sol measured |
| SimpleQA Verified | 69.7% | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: science | 1455 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: medicine and healthcare | 1430 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: legal and government | 1473 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: business and finance | 1456 | Not measured | Only GPT-5.6 Sol measured |
| FACTS Benchmark Suite | 56.5% | Not measured | Only GPT-5.6 Sol measured |
| PRBench Finance | 50.4% | Not measured | Only GPT-5.6 Sol measured |
| PRBench Legal | 50.5% | Not measured | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index16
| Benchmark | GPT-5.6 Sol | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| Design Arena: websites | 1320 | 1325 | Kimi K3.1 Pro |
| Design Arena: UI components | 1332 | 1400 | Kimi K3.1 Pro |
| Design Arena: game dev | 1367 | 1410 | Kimi K3.1 Pro |
| Design Arena: data viz | 1324 | 1300 | GPT-5.6 Sol |
| Design Arena: 3D | 1383 | 1451 | Kimi K3.1 Pro |
| Design Arena: all code categories | 1340 | 1354 | Kimi K3.1 Pro |
| Design Arena: SVG | 1311 | 1328 | Kimi K3.1 Pro |
| Design Arena: ASCII art | 1308 | Not measured | Only GPT-5.6 Sol measured |
| LiveBench design | Not measured | 77.8% | Only Kimi K3.1 Pro measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.6 Sol | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| Vals Index | Not measured | 62.5% | Only Kimi K3.1 Pro measured |
| LiveBench data analysis | Not measured | 79.1% | Only Kimi K3.1 Pro measured |
| Public Benefits Bench (Vals AI) | 66.5% | Not measured | Only GPT-5.6 Sol measured |
| MedScribe (Vals AI) | 85.2% | Not measured | Only GPT-5.6 Sol measured |
| Vals Multimodal Index | 72.6% | Not measured | Only GPT-5.6 Sol measured |
| IFBench | 72.7% | Not measured | Only GPT-5.6 Sol measured |
| Long context reasoning (AA-LCR) | 84.0% | 86.3% | Kimi K3.1 Pro |
| DTBench | 95.7% | Not measured | Only GPT-5.6 Sol measured |
| LMCA | 58.5% | Not measured | Only GPT-5.6 Sol measured |
| Surface Evolver Bench | 93.1% | Not measured | Only GPT-5.6 Sol measured |
| Furniture assembly | 56.7% | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text | 1457 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: instruction following | 1483 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: creative writing | 1450 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Vision | 1281 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: English | 1458 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: non-English | 1450 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: Chinese | 1526 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: German | 1473 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: Japanese | 1472 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: Korean | 1442 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: French | 1473 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: Spanish | 1443 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: Russian | 1472 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: Polish | 1453 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: multi-turn | 1461 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: longer queries | 1480 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: writing and language | 1464 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Text: entertainment and media | 1450 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Vision: English | 1280 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Vision: Chinese | 1313 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Vision: reading text | 1290 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Vision: humor | 1246 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Vision: creative writing | 1283 | Not measured | Only GPT-5.6 Sol measured |
| LMArena Document | 1483 | Not measured | Only GPT-5.6 Sol measured |
| EQ-Bench 4 | 1236 | Not measured | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.6 Sol | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| 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
Kimi K3.1 Pro$0.0070Fits in one request
Kimi K3.1 Pro costs less
Repository review
50K input + 3K output tokens
GPT-5.6 Sol$0.260Fits in one request
Kimi K3.1 Pro$0.130Fits in one request
Kimi K3.1 Pro costs less
Agent loop
200K input + 10K output tokens
GPT-5.6 Sol$1.00Fits in one request
Kimi K3.1 Pro$0.500Fits in one request
Kimi K3.1 Pro 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.
| Specification | OpenAI GPT-5.6 Sol | MoonshotAI Kimi K3.1 Pro |
|---|---|---|
| Maker | OpenAI | Moonshot AI |
| Weights | No public weights listed | No public weights listed |
| Released | July 9, 2026 | October 23, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $4.00 | $2.00 |
| Output $/Mtok | $20.00 | $10.00 |
| Coding index | 70.7 | 82.2 |
| Independent measurements behind it | 5 | 4 |
| Cost per solved task | $1.20 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.6 Sol better than Kimi K3.1 Pro for coding?
Pick Kimi K3.1 Pro for coding: it scores 82.2 on the Vibe Coding Index against 70.7 for GPT-5.6 Sol, though on 4 benchmarks against 5. Pick GPT-5.6 Sol for a larger context window (1.05M against 1.05M tokens) and work measured by IOI (Vals AI) or ALE-Bench, where it leads.
Which is cheaper, GPT-5.6 Sol or Kimi K3.1 Pro?
GPT-5.6 Sol costs $4.00 per million input tokens and $20.00 per million output tokens; Kimi K3.1 Pro costs $2.00 and $10.00. Cost per solved task is known for GPT-5.6 Sol only.
Which has the bigger context window, GPT-5.6 Sol or Kimi K3.1 Pro?
GPT-5.6 Sol, with 1.05M tokens against 1.05M.
How many benchmarks is the GPT-5.6 Sol vs Kimi K3.1 Pro comparison based on?
25 benchmarks have a result for both models as of October 29, 2026. GPT-5.6 Sol's coding index rests on 5 independent benchmarks and Kimi K3.1 Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.