BenchLeader

GPT-6.1 Sol vs Grok 4.20

Verdict
  • GPT-6.1 Sol (max) leads on quality: 69.3 vs 59.0.
  • GPT-6.1 Sol (max) is stronger in agents & tools, coding, composite, human preference, knowledge, long context, maths, multimodal, reasoning.
  • Grok 4.20 (thinking) is stronger in instruction following.
  • Grok 4.20 (thinking) is 1.3× cheaper ($3.00 vs $4.00 per 1M blended).
  • Grok 4.20 (thinking) streams 1.9× faster (103 vs 56 tokens per second).
MetricGPT-6.1 Sol (max)Grok 4.20 (thinking)
BenchLeader Index69.359.0
Agents & tools score63.951.7
Coding score72.453.9
Composite score79.058.5
Human preference score68.166.6
Knowledge score78.856.2
Long context score66.859.5
Maths score72.554.4
Multimodal score66.258.8
Reasoning score76.459.4
Instruction following score–79.9
Blended price $/M$4.00$3.00
Output speed56 tok/s103 tok/s
Time to first answer326.9 s18.5 s
Context window1.1M2M
GPQA Diamond95.4%89.3%
FrontierMath Tiers 1–393.7%44.9%
FrontierMath Tier 4100.0%17.1%
OTIS Mock AIME100.0%92.2%
SimpleQA Verified73.9%30.2%
Terminal-Bench58.2%–
SciCode54.2%–
APEX-Agents60.0%–
ProofBench–14.0%
LMArena Text14841472
LMArena Hard Prompts15071489
LMArena Coding15451511
LMArena WebDev17551375
LMArena Vision12881263
LMArena Agent11.7–
LiveBench81.6%–
LiveBench Reasoning92.6%–
LiveBench Coding80.4%–
LiveBench Agentic Coding54.5%–
LiveBench Mathematics96.8%–
LiveBench Data Analysis82.7%–
LiveBench Language90.1%–
LiveBench Instruction Following74.2%–
AA Intelligence Index v4.3.251.825.7
IFBench–82.9%
AA-LCR83.0%69.0%
MMMU-Pro86.0%74.6%
AA-Omniscience41.514.8
Terminal-Bench Hard–40.9%
GPQA Diamond (AA)–91.1%
Humanity's Last Exam (AA)52.9%34.5%
SciCode (AA)54.2%–
τ²-Bench Telecom (AA)–96.5%
AIME (Vals)–96.5%
LiveCodeBench–84.3%
MMLU-Pro–86.3%
IOI96.9%–
LegalBench–77.7%
CorpFin–63.7%
TaxEval–74.1%
MedQA–94.5%
Terminal-Bench 2.1 (Vals)–44.2%
SWE-bench (Vals)–72.2%
GPQA Diamond (Vals)–88.6%
Vals Index61.1–
Kagi LLM Benchmark–75.0%
ARC-AGI-196.5%89.5%
ARC-AGI-294.2%65.1%
ARC-AGI-396.2%0.1%
CritPt31.7%6.6%
GDPval-AA v2.153.8%–
Analyst Agent (AA)50.0%–
APEX-Agents (AA)–14.2%
BioMysteryBench79.6%–
CaseLaw v2–54.5%
Code Migration65.1%0.3%
CyberBench39.3%–
Excel Modeling Benchmark70.8%11.7%
Finance Agent v252.0%28.5%
Harvey's Legal Agent Benchmark5.4%0.0%
Legal Research Bench38.5%13.9%
MedCode48.8%32.2%
MedScribe86.5%63.4%
MMMU-Pro (Vals)–83.5%
MortgageTax–45.4%
MysteryMechanism46.4%–
Public Benefits Bench59.3%–
SAGE46.5%38.2%
SREBench50.8%–
Tax Agent Bench62.3%31.2%
Terminal-Bench 2.0 (Vals)–40.5%
Terminal-Bench 4.0 (Vals)55.0%–
Vals Multimodal Index–39.1%
Vibe Code Bench v1.188.9%4.1%
LMArena Maths14881465
LMArena Creative Writing14621445
LMArena Instruction Following14881447
LMArena Multi-turn14871479
LMArena Longer Queries14961466
LMArena Document–1439
Chess Puzzles61.0%24.0%
EBR-bench54.3%–
Mystery Game Puzzles80.0%–
ForecastBench–60.7%
Terminal-Bench 4.0 (AA)56.1%–
AutomationBench64.9%–
GDP.pdf31.0%–
MLCR33.9%–
Harvey LAB6.9%–
AA-Omniscience: accuracy62.1%28.9%
AA-Omniscience: non-hallucination45.7%82.6%
AA-Briefcase v1.11557–

Data as of 2026-10-11. Best configuration of each model; every score links to its source on the model pages.

GPT-6.1 Sol vs Grok 4.20: questions

Is GPT-6.1 Sol better than Grok 4.20?
GPT-6.1 Sol (max) leads on quality: 69.3 vs 59.0. The BenchLeader Index combines every independent quality benchmark; GPT-6.1 Sol (max) is ahead overall as of 2026-10-11, but check the category scores for your use.
Is GPT-6.1 Sol better than Grok 4.20 for coding?
GPT-6.1 Sol scores higher in coding (72 vs 54 on the category index, where 50 is average).
Is GPT-6.1 Sol better than Grok 4.20 for agentic tasks?
GPT-6.1 Sol scores higher in agentic tasks (64 vs 52 on the category index, where 50 is average).
Which is cheaper, GPT-6.1 Sol or Grok 4.20?
Grok 4.20 is cheaper: $3.00 against $4.00 per million tokens, blended at three input tokens per output token.
Which is faster, GPT-6.1 Sol or Grok 4.20?
Grok 4.20 streams faster: 103 against 56 output tokens per second.
Which has the larger context window?
Grok 4.20 accepts more context: 2M against 1.1M tokens.