BenchLeader

GPT-6.1 Sol vs Kimi K3.1 Pro Together

Full profiles: GPT-6.1 Sol (OpenAI) and Kimi K3.1 Pro Together (Moonshot AI): every benchmark, price and rank.

Updated · Data from 12 sources

As of 9 Nov 2026, GPT-6.1 Sol is ahead of Kimi K3.1 Pro Together on quality (67.0 vs 60.5 on the BenchLeader Index). GPT-6.1 Sol leads in every category we measure both in.

Key facts (as of 9 Nov 2026)

  • GPT-6.1 Sol scores 67.0 on the BenchLeader Index and Kimi K3.1 Pro Together scores 60.5 (BenchLeader, 9 Nov 2026).
  • GPT-6.1 Sol costs $4.00 per 1M tokens blended (list price, 9 Nov 2026).
  • Of the 7 benchmarks both models have, GPT-6.1 Sol leads 6 (BenchLeader, 9 Nov 2026).

Which to pick for…

The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.

Use casePickWhyConfidence
MathsGPT-6.1 Sol72 vs 66 category score; FrontierMath Tiers 1–3 93.7% vs 78.3%Medium
ReasoningGPT-6.1 Sol72 vs 67 category score; GPQA Diamond 95.4% vs 94.2%Medium
KnowledgeGPT-6.1 Sol73 vs 68 category score; SimpleQA Verified 73.9% vs 62.2%Medium
Chat quality (human preference)–Only GPT-6.1 Sol has an Arena rating (67 category score)Not comparable
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • GPT-6.1 Sol (max) leads on quality: 67.0 vs 60.5.
  • GPT-6.1 Sol (max) is stronger in agents & tools, coding, human preference, knowledge, long context, maths, multimodal, reasoning.

At a glance

SpecGPT-6.1 SolKimi K3.1 Pro Together
DeveloperOpenAIMoonshot AI
Released29 Sep 202623 Oct 2026
Context window (tokens)1,050,000–
Compared atGPT-6.1 Sol (max)Kimi K3.1 Pro Together (max)
Open weightsNoNo
Price in / out / cached input per 1M$2.00 / $10.00 / $0.100–

Category by category

Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.

CategoryGPT-6.1 Sol (max)Kimi K3.1 Pro Together (max)Leader
Reasoning71.867.1GPT-6.1 Sol
Coding71.4–not comparable
Agents & tools64.7–not comparable
Maths72.165.8GPT-6.1 Sol
Knowledge72.767.6GPT-6.1 Sol
Human preference67.3–not comparable
Multimodal65.7–not comparable
Long context66.3–not comparable

On one chart

Each domain on the index's own scale, where 50 is an average model. Click a domain to see the benchmarks behind it. Pick up to 5 models from the list.

2550 avg75ReasoningMathsKnowledgeGPT-6.1 Sol, Reasoning: 71.8GPT-6.1 Sol, Maths: 72.1GPT-6.1 Sol, Knowledge: 72.7Kimi K3.1 Pro Together, Reasoning: 67.1Kimi K3.1 Pro Together, Maths: 65.8Kimi K3.1 Pro Together, Knowledge: 67.6

Not drawn, measured for fewer than two of these models: Coding, Agents & tools, Instruction following, Long context, Multimodal, Human preference.

ModelIndex

Where sources disagree

Across the 7 benchmarks both have, GPT-6.1 Sol leads 6, Kimi K3.1 Pro Together leads 0 and 1 is a tie. Every overall index that rates both puts GPT-6.1 Sol ahead.

Overall indexGPT-6.1 Sol (max)Kimi K3.1 Pro Together (max)Leader
BenchLeader Index67.060.5GPT-6.1 Sol

Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).

Price, speed and latency

List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page. Cost, tokens and time per benchmark task are measured: Artificial Analysis’ averages over its whole Intelligence Index run.

MeasureGPT-6.1 Sol (max)Kimi K3.1 Pro Together (max)
Blended price per 1M tokens$4.00–
Input / output per 1M$2.00 / $10.00– / –
Cached input per 1M$0.100–
Price per task: chat reply$0.0038–
Price per task: summarize a 30-page report$0.030–
Price per task: code edit$0.027–
Price per task: agentic coding session$0.160–
Price per task: structured extraction$0.0060–
Agentic coding session, input mostly cached$0.074–
Cost per benchmark task (AA Index)$1.27–
Output tokens per task (AA Index)68k–
Of which reasoning49k–
Time per task (AA Index)20 min–
Output speed57 tok/s–
Time to first answer161.1 s–
Time to a complete answer377.5 s–

Each model is compared at its best-ranked reasoning-effort setting. GPT-6.1 Sol (max) scores 67.0 and takes 161 s to its first answer token; GPT-6.1 Sol (xhigh) scores 63.8 in 62 s, GPT-6.1 Sol (high) scores 63.5 in 33 s. Kimi K3.1 Pro Together (max) scores 60.5. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.

Every benchmark

119 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.

MetricPublisherGPT-6.1 Sol (max)Kimi K3.1 Pro Together (max)
BenchLeader IndexBenchLeader67.060.5
Agents & tools scoreBenchLeader64.7–
Coding scoreBenchLeader71.4–
Human preference scoreBenchLeader67.3–
Knowledge scoreBenchLeader72.767.6
Long context scoreBenchLeader66.3–
Maths scoreBenchLeader72.165.8
Multimodal scoreBenchLeader65.7–
Reasoning scoreBenchLeader71.867.1
Blended price $/MBenchLeader$4.00–
Output speedBenchLeader57 tok/s–
Time to first answerBenchLeader161.1 s–
Context windowBenchLeader1,050,000 tokens–
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub95.4%94.2%
Arena Hard PromptsArena (LMArena)1506–
LiveBench 2.0 ReasoningLiveBench92.6%†–
LiveBench 1.0 ReasoningLiveBench92.6%–
Humanity's Last Exam (AA)Artificial Analysis52.9%–
HLE-Diamond (AA)Artificial Analysis58.8%–
ARC-AGI-1ARC Prize96.5%–
ARC-AGI-2ARC Prize94.2%–
ARC-AGI-3ARC Prize96.2%–
CritPtArtificial Analysis31.7%–
CritPt v2 hard subset (AA)Artificial Analysis69.5%–
MysteryMechanismVals AI46.4%–
Chess PuzzlesEpoch AI Benchmarking Hub68.0%45.0%
Mystery Game PuzzlesEpoch AI Benchmarking Hub80.0%42.0%
LMCAEpoch AI Benchmarking Hub62.8%–
DTBenchEpoch AI Benchmarking Hub96.5%–
Coding
SciCodeSciCode54.2%–
FrontierCodeCognition50.2%†–
Arena CodingArena (LMArena)1541–
Arena WebDevArena (LMArena)1743–
LiveBench 2.0 CodingLiveBench82.1%†–
LiveBench 1.0 CodingLiveBench80.4%–
IOIVals AI96.9%–
Code MigrationVals AI65.1%–
Code Migration v1.1Vals AI77.3%–
Show all 119 benchmarks
MetricPublisherGPT-6.1 Sol (max)Kimi K3.1 Pro Together (max)
Coding
ProgramBenchVals AI3.0%–
SWE-bench MultimodalVals AI43.5%–
Vibe Code Bench v1.1Vals AI88.9%–
ALE-BenchEpoch AI Benchmarking Hub2743.8–
Terminal-Bench 4.0 (AA)Artificial Analysis56.1%–
Startrise FrontendStartrise78.6%†–
GameBench 2 OverallDuelLab GameBench 284.8†–
GameBench 2 by reasoning settingDuelLab GameBench 292.0†–
Design Arena WebsiteDesign Arena1310†–
FrontierCode 1.1 (AA)Artificial Analysis49.1%–
FrontierCode 2.0 (AA)Artificial Analysis40.6%–
Agents & tools
Terminal-BenchTerminal-Bench60.9%–
APEX-AgentsMercor60.0%–
Arena AgentArena (LMArena)12.5–
LiveBench Long AgenticLiveBench65.6%†–
LiveBench BrowserLiveBench93.3%†–
LiveBench Agentic CodingLiveBench54.5%–
HiL-BenchScale AI SEAL62.3%†–
GDPval-AA v2.1, normalised scoreArtificial Analysis54.8%–
GDPval-AA v2.1Artificial Analysis1609–
Analyst Agent (AA)Artificial Analysis50.0%–
CyberBenchVals AI39.3%–
Finance Agent v2Vals AI52.0%–
Finance Agent v2.1Vals AI61.8%–
Harvey's Legal Agent Benchmark v1.1Vals AI6.3%–
Harvey's Legal Agent Benchmark v1Vals AI5.4%–
Legal Research BenchVals AI38.5%–
Robo-benchVals AI28.3%–
SREBenchVals AI50.8%–
Tax Agent BenchVals AI21.8%–
Terminal-Bench 4.0 (Vals)Vals AI55.0%–
Terminal-Bench ScienceVals AI52.9%–
Arena SearchArena (LMArena)1249–
AutomationBenchArtificial Analysis64.9%–
GDP.pdf (AA)Artificial Analysis31.0%–
Harvey LAB-AA v1.1Harvey6.9%–
AA-Briefcase v1.1Artificial Analysis1555–
GDPxGDPx by SemiAnalysis8.4%–
Design Arena AgenticDesign Arena1425–
Terminal-Bench-Science 0.1 (AA)Artificial Analysis58.1%–
FACTS SearchGoogle92.8%†–
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub93.7%78.3%
FrontierMath Tier 4Epoch AI Benchmarking Hub100.0%65.8%
OTIS Mock AIMEEpoch AI Benchmarking Hub100.0%100.0%
ProofBenchVals AI99.0%†–
LiveBench MathematicsLiveBench96.8%–
Arena MathsArena (LMArena)1498–
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub73.9%62.2%
LiveBench 2.0 Data AnalysisLiveBench82.7%†–
LiveBench ResearchLiveBench90.0%†–
LiveBench 1.0 Data AnalysisLiveBench82.7%–
AA-Omniscience v1.1Artificial Analysis42.0–
PRBench FinanceScale AI SEAL46.2%†–
PRBench LegalScale AI SEAL47.9%†–
BioMysteryBenchVals AI79.6%–
ClaimBenchVals AI100.0%–
Excel Modeling BenchmarkVals AI70.8%–
Excel Modeling Benchmark v1.1Vals AI71.1%–
MedCodeVals AI48.8%–
MedScribeVals AI86.5%–
Public Benefits Bench v1.1Vals AI59.3%–
EBR-benchEpoch AI Benchmarking Hub54.3%–
GDP.pdfEpoch AI Benchmarking Hub35.0%–
AA-Omniscience v1.1: accuracyArtificial Analysis61.8%–
AA-Omniscience v1.1: non-hallucinationArtificial Analysis48.1%–
HealthBench Professional (AA)OpenAI65.1%–
Instruction following
LiveBench LanguageLiveBench90.1%–
LiveBench Instruction FollowingLiveBench74.2%–
MultiChallengeScale AI SEAL82.0%†–
Arena Instruction FollowingArena (LMArena)1484–
Human preference
Arena TextArena (LMArena)1482–
EQ-Bench 4EQ-Bench1272†–
Arena Creative WritingArena (LMArena)1449–
Arena Multi-turnArena (LMArena)1486–
Arena Longer QueriesArena (LMArena)1489–
Multimodal
Arena VisionArena (LMArena)1286–
LiveBench DesignLiveBench79.6%†–
MMMU-ProArtificial Analysis86.0%–
SAGEVals AI90.5%–
Code2Video-AAArtificial Analysis1369–
AA-3DArtificial Analysis1121–
Long context
AA-LCR v1.1Artificial Analysis83.0%–
MLCRArtificial Analysis38.3%–
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub168.9†–
LiveBench 2.0LiveBench81.4%†–
LiveBench 1.0LiveBench81.6%–
AA Intelligence Index v5.0Artificial Analysis54.6–
AA Intelligence Index v4.3.2Artificial Analysis51.8–
AA Progress Index v1Artificial Analysis348.5–
Vals IndexVals AI63.9–
Vals Finance IndexVals AI55.8%–
Vals RSI IndexVals AI26.6%–
Vals Science IndexVals AI59.6%–
Vals Router IndexVals AI63.9%†–

Data as of 2026-11-09. Best configuration of each model; every score links to its source on the model pages.

DuelLab GameBench 2, release gb2-20261103-eaea31df94e6 (https://benchmarks.duellab.org/releases/gb2-20261103-eaea31df94e6/), CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Scores mapped to BenchLeader model names; not endorsed by DuelLab.

What changed

  • GPT-6.1 Sol (max): 2 score revisions.
  • GPT-6.1 Sol (max): 3 score revisions.
  • Kimi K3.1 Pro Together (max): first results.
  • GPT-6.1 Sol (max): 1 score revision.
  • GPT-6.1 Sol (max): 1 new result (MirrorCode).
  • GPT-6.1 Sol (max): 1 score revision.
  • GPT-6.1 Sol (max): 5 new results (AA Intelligence Index v5.0, AA Progress Index v1, HLE-Diamond (AA)…); 3 score revisions; cost per task moved from $0.72/M to $1.27/M (76% up).
  • GPT-6.1 Sol (max): 10 new results (ClaimBench, Code Migration v1.1, Excel Modeling Benchmark v1.1…).
  • GPT-6.1 Sol (max): BenchLeader Index 67.9 → 67.4.
  • GPT-6.1 Sol (max): 5 score revisions.

Rankings: Best LLM overall · Best LLM for coding · Best LLM for agents · Best cheap LLMs

GPT-6.1 Sol vs Kimi K3.1 Pro Together: questions

Is GPT-6.1 Sol better than Kimi K3.1 Pro Together?
GPT-6.1 Sol (max) leads on quality: 67.0 vs 60.5. The BenchLeader Index combines every independent quality benchmark; GPT-6.1 Sol (max) is ahead overall as of 9 Nov 2026, but check the category scores for your use.
Do independent benchmarks agree on GPT-6.1 Sol vs Kimi K3.1 Pro Together?
Across the 7 benchmarks both have, GPT-6.1 Sol leads 6, Kimi K3.1 Pro Together leads 0 and 1 is a tie. Every overall index that rates both puts GPT-6.1 Sol ahead.
When was Kimi K3.1 Pro Together released?
Kimi K3.1 Pro Together was released on 23 Oct 2026.