GPT-6.1 Sol vs Grok 4.20 Multi-Agent
Full profiles: GPT-6.1 Sol (OpenAI) and Grok 4.20 Multi-Agent (SpaceXAI): every benchmark, price and rank.
Updated · Data from 9 sources
As of 29 Oct 2026, GPT-6.1 Sol is ahead of Grok 4.20 Multi-Agent on quality (67.2 vs 58.5 on the BenchLeader Index), but Grok 4.20 Multi-Agent is 2.6× cheaper at $1.56 vs $4.00 per 1M tokens blended. GPT-6.1 Sol leads in every category we measure both in. Grok 4.20 Multi-Agent streams 3×+ faster.
Key facts (as of 29 Oct 2026)
- GPT-6.1 Sol scores 67.2 on the BenchLeader Index and Grok 4.20 Multi-Agent scores 58.5 (BenchLeader, 29 Oct 2026).
- GPT-6.1 Sol costs $4.00 per 1M tokens blended (list price, 29 Oct 2026).
- Grok 4.20 Multi-Agent costs $1.56 per 1M tokens blended (list price, 29 Oct 2026).
- Grok 4.20 Multi-Agent streams 3×+ faster than GPT-6.1 Sol (Artificial Analysis, 7-day median, 29 Oct 2026).
- Of the 9 benchmarks both models have, GPT-6.1 Sol leads 9 (BenchLeader, 29 Oct 2026).
GPT-6.1 Sol benchmarks max OpenAI
Grok 4.20 Multi-Agent benchmarks SpaceXAIOpen in the comparison toolWhich 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 case | Pick | Why | Confidence |
|---|---|---|---|
| Coding | GPT-6.1 Sol | 72 vs 64 category score; Arena Coding 1537 vs 1508 | Medium |
| Maths | GPT-6.1 Sol | 73 vs 63 category score; Arena Maths 1513 vs 1455 | High |
| Reasoning | GPT-6.1 Sol | 73 vs 65 category score; Arena Hard Prompts 1504 vs 1484 | High |
| Images and other media | GPT-6.1 Sol | 66 vs 59 category score; Arena Vision 1288 vs 1259 | Medium |
| Chat quality (human preference) | GPT-6.1 Sol | 67 vs 66 on Arena votes | Medium |
| Lowest cost | Grok 4.20 Multi-Agent | $1.56 vs $4.00 per 1M blended; agentic coding session $0.085 vs $0.160 | – |
| Fastest first answer | Grok 4.20 Multi-Agent | 7.1 s (Grok 4.20 Multi-Agent) vs 249.5 s (GPT-6.1 Sol (max)) to the first answer token | – |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- GPT-6.1 Sol (max) leads on quality: 67.2 vs 58.5.
- GPT-6.1 Sol (max) is stronger in agents & tools, coding, human preference, knowledge, long context, maths, multimodal, reasoning.
- Grok 4.20 Multi-Agent is 2.6× cheaper ($1.56 vs $4.00 per 1M blended).
- Grok 4.20 Multi-Agent streams 4.6× faster (360 vs 79 tokens per second).
At a glance
| Spec | GPT-6.1 Sol | Grok 4.20 Multi-Agent |
|---|---|---|
| Developer | OpenAI | SpaceXAI |
| Released | 29 Sept 2026 | 9 Mar 2026 |
| Context window (tokens) | 1,050,000 | 2,000,000 |
| Compared at | GPT-6.1 Sol (max) | Grok 4.20 Multi-Agent |
| Open weights | No | No |
| Price in / out / cached input per 1M | $2.00 / $10.00 / $0.100 | $1.25 / $2.50 / $0.200 |
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.
| Category | GPT-6.1 Sol (max) | Grok 4.20 Multi-Agent | Leader |
|---|---|---|---|
| Reasoning | 73.2 | 64.8 | GPT-6.1 Sol |
| Coding | 71.6 | 64.4 | GPT-6.1 Sol |
| Agents & tools | 64.4 | – | not comparable |
| Maths | 72.8 | 63.3 | GPT-6.1 Sol |
| Knowledge | 73.0 | – | not comparable |
| Human preference | 67.1 | 66.0 | GPT-6.1 Sol |
| Multimodal | 65.9 | 59.3 | GPT-6.1 Sol |
| Long context | 66.4 | – | not comparable |
Where sources disagree
Across the 9 benchmarks both have, GPT-6.1 Sol leads 9, Grok 4.20 Multi-Agent leads 0. Every overall index that rates both puts GPT-6.1 Sol ahead.
| Overall index | GPT-6.1 Sol (max) | Grok 4.20 Multi-Agent | Leader |
|---|---|---|---|
| BenchLeader Index | 67.2 | 58.5 | GPT-6.1 Sol |
| Arena Text | 1480 | 1471 | GPT-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; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.
| Measure | GPT-6.1 Sol (max) | Grok 4.20 Multi-Agent |
|---|---|---|
| Blended price per 1M tokens | $4.00 | $1.56 |
| Input / output per 1M | $2.00 / $10.00 | $1.25 / $2.50 |
| Cached input per 1M | $0.100 | $0.200 |
| Price per task: chat reply | $0.0038 | $0.0013 |
| Price per task: summarize a 30-page report | $0.030 | $0.017 |
| Price per task: code edit | $0.027 | $0.011 |
| Price per task: agentic coding session | $0.160 | $0.085 |
| Price per task: structured extraction | $0.0060 | $0.0030 |
| Cost to run a full benchmark suite | $1.27 | – |
| Output speed | 79 tok/s | 360 tok/s |
| Time to first answer | 249.5 s | 7.1 s |
| Time to a complete answer | 255.8 s | – |
Each model is compared at its best-ranked reasoning-effort setting. GPT-6.1 Sol (max) scores 67.2 and takes 249 s to its first answer token; GPT-6.1 Sol (xhigh) scores 64.3 in 97 s, GPT-6.1 Sol (high) scores 64.0 in 28 s. Grok 4.20 Multi-Agent scores 58.5 and takes 7 s to its first answer token. 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
114 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.
| Metric | Publisher | GPT-6.1 Sol (max) | Grok 4.20 Multi-Agent |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 67.2 | 58.5 |
| Agents & tools score | BenchLeader | 64.4 | – |
| Coding score | BenchLeader | 71.6 | 64.4 |
| Human preference score | BenchLeader | 67.1 | 66.0 |
| Knowledge score | BenchLeader | 73.0 | – |
| Long context score | BenchLeader | 66.4 | – |
| Maths score | BenchLeader | 72.8 | 63.3 |
| Multimodal score | BenchLeader | 65.9 | 59.3 |
| Reasoning score | BenchLeader | 73.2 | 64.8 |
| Blended price $/M | BenchLeader | $4.00 | $1.56 |
| Output speed | BenchLeader | 79 tok/s | 360 tok/s |
| Time to first answer | BenchLeader | 249.5 s | 7.1 s |
| Context window | BenchLeader | 1,050,000 tokens | 2,000,000 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 95.4% | – |
| Arena Hard Prompts | Arena (LMArena) | 1504 | 1484 |
| LiveBench 2.0 Reasoning | LiveBench | 92.6%† | – |
| LiveBench 1.0 Reasoning | LiveBench | 92.6% | – |
| Humanity's Last Exam (AA) | Artificial Analysis | 52.9% | – |
| HLE-Diamond (AA) | Artificial Analysis | 58.8% | – |
| ARC-AGI-1 | ARC Prize | 96.5% | – |
| ARC-AGI-2 | ARC Prize | 94.2% | – |
| ARC-AGI-3 | ARC Prize | 96.2% | – |
| CritPt | Artificial Analysis | 31.7% | – |
| CritPt v2 hard subset (AA) | Artificial Analysis | 68.5% | – |
| MysteryMechanism | Vals AI | 46.4% | – |
| Chess Puzzles | Epoch AI Benchmarking Hub | 68.0% | – |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 80.0% | – |
| LMCA | Epoch AI Benchmarking Hub | 62.8% | – |
| DTBench | Epoch AI Benchmarking Hub | 96.5% | – |
| Coding | |||
| SciCode | SciCode | 54.2% | – |
| FrontierCode | Cognition | 50.2%† | – |
| Arena Coding | Arena (LMArena) | 1537 | 1508 |
| Arena WebDev | Arena (LMArena) | 1752 | – |
| LiveBench 2.0 Coding | LiveBench | 96.0%† | – |
| LiveBench 1.0 Coding | LiveBench | 80.4% | – |
| IOI | Vals AI | 96.9% | – |
| Code Migration | Vals AI | 65.1% | – |
| Code Migration v1.1 | Vals AI | 77.3% | – |
Show all 114 benchmarks
| Metric | Publisher | GPT-6.1 Sol (max) | Grok 4.20 Multi-Agent |
|---|---|---|---|
| Coding | |||
| ProgramBench | Vals AI | 3.0% | – |
| SWE-bench Multimodal | Vals AI | 43.5% | – |
| Vibe Code Bench v1.1 | Vals AI | 88.9% | – |
| ALE-Bench | Epoch AI Benchmarking Hub | 2743.8 | – |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 56.1% | – |
| Startrise Frontend | Startrise | 78.6%† | – |
| FrontierCode 1.1 (AA) | Artificial Analysis | 49.1% | – |
| FrontierCode 2.0 (AA) | Artificial Analysis | 40.6% | – |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 58.2% | – |
| APEX-Agents | Mercor | 60.0% | – |
| Arena Agent | Arena (LMArena) | 13.6 | – |
| LiveBench Long Agentic | LiveBench | 68.7%† | – |
| LiveBench Browser | LiveBench | 93.3%† | – |
| LiveBench Agentic Coding | LiveBench | 54.5% | – |
| HiL-Bench | Scale AI SEAL | 62.3%† | – |
| GDPval-AA v2.1, normalised score | Artificial Analysis | 54.8% | – |
| GDPval-AA v2.1 | Artificial Analysis | 1608 | – |
| Analyst Agent (AA) | Artificial Analysis | 50.0% | – |
| CyberBench | Vals AI | 39.3% | – |
| Finance Agent v2 | Vals AI | 52.0% | – |
| Finance Agent v2.1 | Vals AI | 61.8% | – |
| Harvey's Legal Agent Benchmark v1.1 | Vals AI | 6.3% | – |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 5.4% | – |
| Legal Research Bench | Vals AI | 38.5% | – |
| Robo-bench | Vals AI | 28.3% | – |
| SREBench | Vals AI | 50.8% | – |
| Tax Agent Bench | Vals AI | 21.8% | – |
| Terminal-Bench 4.0 (Vals) | Vals AI | 55.0% | – |
| Terminal-Bench Science | Vals AI | 52.9% | – |
| Arena Search | Arena (LMArena) | 1250 | 1206 |
| AutomationBench | Artificial Analysis | 64.9% | – |
| GDP.pdf (AA) | Artificial Analysis | 31.0% | – |
| Harvey LAB-AA v1.1 | Harvey | 6.9% | – |
| AA-Briefcase v1.1 | Artificial Analysis | 1555 | – |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 58.1% | – |
| FACTS Search | 88.2%† | – | |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 93.7% | – |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 100.0% | – |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 100.0% | – |
| ProofBench | Vals AI | 99.0%† | – |
| LiveBench Mathematics | LiveBench | 96.8% | – |
| Arena Maths | Arena (LMArena) | 1513 | 1455 |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 73.9% | – |
| LiveBench 2.0 Data Analysis | LiveBench | 82.7%† | – |
| LiveBench Research | LiveBench | 83.5%† | – |
| LiveBench 1.0 Data Analysis | LiveBench | 82.7% | – |
| AA-Omniscience v1.1 | Artificial Analysis | 42.0 | – |
| PRBench Finance | Scale AI SEAL | 46.2%† | – |
| PRBench Legal | Scale AI SEAL | 47.9%† | – |
| BioMysteryBench | Vals AI | 79.6% | – |
| ClaimBench | Vals AI | 100.0% | – |
| Excel Modeling Benchmark | Vals AI | 70.8% | – |
| Excel Modeling Benchmark v1.1 | Vals AI | 71.1% | – |
| MedCode | Vals AI | 48.8% | – |
| MedScribe | Vals AI | 86.5% | – |
| Public Benefits Bench v1.1 | Vals AI | 59.3% | – |
| EBR-bench | Epoch AI Benchmarking Hub | 54.3% | – |
| GDP.pdf | Epoch AI Benchmarking Hub | 35.0% | – |
| AA-Omniscience v1.1: accuracy | Artificial Analysis | 61.8% | – |
| AA-Omniscience v1.1: non-hallucination | Artificial Analysis | 48.1% | – |
| HealthBench Professional (AA) | OpenAI | 65.1% | – |
| Instruction following | |||
| LiveBench Language | LiveBench | 90.1% | – |
| LiveBench Instruction Following | LiveBench | 74.2% | – |
| MultiChallenge | Scale AI SEAL | 82.0%† | – |
| Arena Instruction Following | Arena (LMArena) | 1485 | 1444 |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1480 | 1471 |
| EQ-Bench 4 | EQ-Bench | 1272† | – |
| Arena Creative Writing | Arena (LMArena) | 1453 | 1447 |
| Arena Multi-turn | Arena (LMArena) | 1483 | 1474 |
| Arena Longer Queries | Arena (LMArena) | 1489 | 1458 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1288 | 1259 |
| LiveBench Design | LiveBench | 82.1%† | – |
| MMMU-Pro | Artificial Analysis | 86.0% | – |
| SAGE | Vals AI | 90.5% | – |
| Code2Video-AA | Artificial Analysis | 1369 | – |
| AA-3D | Artificial Analysis | 1119 | – |
| Long context | |||
| AA-LCR v1.1 | Artificial Analysis | 83.0% | – |
| MLCR | Artificial Analysis | 38.3% | – |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 168.4† | – |
| LiveBench 2.0 | LiveBench | 84.1%† | – |
| LiveBench 1.0 | LiveBench | 81.6% | – |
| AA Intelligence Index v5.0 | Artificial Analysis | 54.5 | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 51.8 | – |
| AA Progress Index v1 | Artificial Analysis | 348.5 | – |
| Vals Index | Vals AI | 63.9 | – |
| Vals Finance Index | Vals AI | 55.8% | – |
| Vals RSI Index | Vals AI | 26.6% | – |
| Vals Science Index | Vals AI | 59.6% | – |
| Vals Router Index | Vals AI | 63.9%† | – |
Data as of 2026-10-29. Best configuration of each model; every score links to its source on the model pages.
What changed
- 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.
- Grok 4.20 Multi-Agent: BenchLeader Index 59.1 → 58.6.
- GPT-6.1 Sol (max): 2 score revisions.
- GPT-6.1 Sol (max): 2 new results (LMCA, DTBench).
- GPT-6.1 Sol (max): 2 score revisions.
- GPT-6.1 Sol (max): 2 new results (ProgramBench, Terminal-Bench Science); 1 score revision.
- GPT-6.1 Sol (max): 3 new results (ALE-Bench, GDP.pdf, Arena Search); 4 score revisions.
Related comparisons
- GPT-6.1 Sol vs Claude Opus 5.5
- GPT-6.1 Sol vs GPT-6 Astra
- GPT-6.1 Sol vs Claude Fable 5.1
- Grok 4.20 Multi-Agent vs Claude Opus 5.5
- Grok 4.20 Multi-Agent vs GPT-6 Astra
- Grok 4.20 Multi-Agent vs Claude Fable 5.1
- GPT-6.1 Sol vs Grok 4.20
- GPT-6.1 Sol vs Gemini 4 Argon
Rankings: Best LLM overall · Best LLM for coding · Best LLM for agents · Best cheap LLMs
GPT-6.1 Sol vs Grok 4.20 Multi-Agent: questions
- Is GPT-6.1 Sol better than Grok 4.20 Multi-Agent?
- GPT-6.1 Sol (max) leads on quality: 67.2 vs 58.5. The BenchLeader Index combines every independent quality benchmark; GPT-6.1 Sol (max) is ahead overall as of 29 Oct 2026, but check the category scores for your use.
- GPT-6.1 Sol vs Grok 4.20 Multi-Agent: which is cheaper, and will that change?
- Grok 4.20 Multi-Agent is cheaper today: $1.56 against $4.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is GPT-6.1 Sol or Grok 4.20 Multi-Agent better for coding?
- GPT-6.1 Sol scores higher in coding (72 vs 64 on the category index, where 50 is average). On Arena Coding, the top shared coding benchmark, it is 1537 for GPT-6.1 Sol against 1508 for Grok 4.20 Multi-Agent.
- Which is faster, GPT-6.1 Sol or Grok 4.20 Multi-Agent?
- Grok 4.20 Multi-Agent streams 3×+ faster (360 vs 79 output tokens per second, Artificial Analysis 7-day median).
- Which is better for long documents?
- Grok 4.20 Multi-Agent accepts more context: 2,000,000 against 1,050,000 tokens for GPT-6.1 Sol.
More questions (3)
- Which has lower latency?
- Grok 4.20 Multi-Agent answers first: 7.1 s against 249.5 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
- Do independent benchmarks agree on GPT-6.1 Sol vs Grok 4.20 Multi-Agent?
- Across the 9 benchmarks both have, GPT-6.1 Sol leads 9, Grok 4.20 Multi-Agent leads 0. Every overall index that rates both puts GPT-6.1 Sol ahead.
- When was GPT-6.1 Sol released?
- GPT-6.1 Sol was released on 29 Sept 2026.