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GPT-5.3-Codex vs GPT-6 Sol

Full profiles: GPT-5.3-Codex (OpenAI) and GPT-6 Sol (OpenAI): every benchmark, price and rank.

Updated · Data from 10 sources

As of 9 Nov 2026, GPT-5.3-Codex and GPT-6 Sol are neck and neck on quality (62.9 vs 62.9 on the BenchLeader Index, inside the ±7.6 margin), and GPT-6 Sol is 1.2× cheaper at $4.00 vs $4.81 per 1M tokens blended. Choose GPT-5.3-Codex for agents & tools (80 vs 60) and fast first answers (42.9 s vs 72.1 s); choose GPT-6 Sol for coding (67 vs 61), where it also streams ~1.5× faster.

Key facts (as of 9 Nov 2026)

  • GPT-5.3-Codex scores 62.9 on the BenchLeader Index and GPT-6 Sol scores 62.9 (BenchLeader, 9 Nov 2026).
  • GPT-5.3-Codex costs $4.81 per 1M tokens blended (list price, 9 Nov 2026).
  • GPT-6 Sol costs $4.00 per 1M tokens blended (list price, 9 Nov 2026).
  • GPT-6 Sol streams ~1.5× faster than GPT-5.3-Codex (Artificial Analysis, 7-day median, 9 Nov 2026).
  • Of the 9 benchmarks both models have, GPT-6 Sol leads 9 (BenchLeader, 9 Nov 2026).
GPT-5.3-Codex benchmarks xhigh OpenAI GPT-6 Sol benchmarks max OpenAIAdd a third model

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
CodingGPT-6 Sol67 vs 61 category score; IOI 82.6% vs 53.8%Medium
Agents & tool useGPT-5.3-Codex80 vs 60 category score; AA-Briefcase v1.1 868 vs 1476High
Long documentsEither66 vs 67 category score; AA-LCR v1.1 83.3% vs 83.7%Either
Images and other mediaEither61 vs 61 category score; MMMU-Pro 78.5% vs 83.0%Either
Chat quality (human preference)–Only GPT-6 Sol has an Arena rating (64 category score)Not comparable
Lowest costGPT-6 Sol$4.00 vs $4.81 per 1M blended; agentic coding session $0.160 vs $0.161–
Fastest first answerGPT-5.3-Codex42.9 s (GPT-5.3-Codex (xhigh)) vs 72.1 s (GPT-6 Sol (max)) to the first answer token–
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • GPT-5.3-Codex (xhigh) and GPT-6 Sol (max) are neck and neck on quality (62.9 vs 62.9, within the ±7.6 margin).
  • GPT-5.3-Codex (xhigh) is stronger in agents & tools, instruction following, multimodal.
  • GPT-6 Sol (max) is stronger in coding, long context, human preference, knowledge, maths, reasoning.
  • GPT-6 Sol (max) is 1.2× cheaper ($4.00 vs $4.81 per 1M blended).
  • GPT-6 Sol (max) streams 1.6× faster (121 vs 77 tokens per second).

At a glance

SpecGPT-5.3-CodexGPT-6 Sol
DeveloperOpenAIOpenAI
Released5 Feb 202622 Sep 2026
Context window (tokens)400,0001,050,000
Compared atGPT-5.3-Codex (xhigh)GPT-6 Sol (max)
Open weightsNoNo
Price in / out / cached input per 1M$1.75 / $14.00 / $0.175$2.00 / $10.00 / $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.

CategoryGPT-5.3-Codex (xhigh)GPT-6 Sol (max)Leader
Reasoning–66.2not comparable
Coding61.066.5GPT-6 Sol
Agents & tools80.159.6GPT-5.3-Codex
Maths–68.5not comparable
Knowledge–61.5not comparable
Instruction following73.6–not comparable
Human preference–64.2not comparable
Multimodal60.960.7level
Long context66.466.6level

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 avg75CodingAgents & toolsLong contextMultimodalGPT-5.3-Codex, Coding: 61.0GPT-5.3-Codex, Agents & tools: 80.1GPT-5.3-Codex, Long context: 66.4GPT-5.3-Codex, Multimodal: 60.9GPT-6 Sol, Coding: 66.5GPT-6 Sol, Agents & tools: 59.6GPT-6 Sol, Long context: 66.6GPT-6 Sol, Multimodal: 60.7

Not drawn, measured for fewer than two of these models: Reasoning, Maths, Knowledge, Instruction following, Human preference.

ModelIndex

Where sources disagree

Across the 9 benchmarks both have, GPT-5.3-Codex leads 0, GPT-6 Sol leads 9.

Overall indexGPT-5.3-Codex (xhigh)GPT-6 Sol (max)Leader
BenchLeader Index62.962.9neck and neck

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-5.3-Codex (xhigh)GPT-6 Sol (max)
Blended price per 1M tokens$4.81$4.00
Input / output per 1M$1.75 / $14.00$2.00 / $10.00
Cached input per 1M$0.175$0.200
Price per task: chat reply$0.0049$0.0038
Price per task: summarize a 30-page report$0.029$0.030
Price per task: code edit$0.032$0.027
Price per task: agentic coding session$0.161$0.160
Price per task: structured extraction$0.0063$0.0060
Agentic coding session, input mostly cached$0.090$0.079
Cost per benchmark task (AA Index)–$2.47
Output tokens per task (AA Index)–54k
Of which reasoning–35k
Time per task (AA Index)–7 min
Output speed77 tok/s121 tok/s
Time to first answer42.9 s72.1 s
Time to a complete answer85.0 s130.2 s

Each model is compared at its best-ranked reasoning-effort setting. GPT-5.3-Codex (xhigh) scores 62.9 and takes 43 s to its first answer token. GPT-6 Sol (max) scores 62.9 and takes 72 s to its first answer token; GPT-6 Sol (xhigh) scores 58.6 in 24 s, GPT-6 Sol (high) scores 58.2 in 9 s. 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

108 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-5.3-Codex (xhigh)GPT-6 Sol (max)
BenchLeader IndexBenchLeader62.962.9
Agents & tools scoreBenchLeader80.159.6
Coding scoreBenchLeader61.066.5
Instruction following scoreBenchLeader73.6–
Long context scoreBenchLeader66.466.6
Multimodal scoreBenchLeader60.960.7
Human preference scoreBenchLeader–64.2
Knowledge scoreBenchLeader–61.5
Maths scoreBenchLeader–68.5
Reasoning scoreBenchLeader–66.2
Blended price $/MBenchLeader$4.81$4.00
Output speedBenchLeader77 tok/s121 tok/s
Time to first answerBenchLeader42.9 s72.1 s
Context windowBenchLeader400,000 tokens1,050,000 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub–94.3%
Arena Hard PromptsArena (LMArena)–1483
LiveBench 1.0 ReasoningLiveBench–88.7%
GPQA Diamond (AA)Artificial Analysis91.5%–
Humanity's Last Exam (AA)Artificial Analysis42.5%47.9%
HLE-Diamond (AA)Artificial Analysis–45.2%
ARC-AGI-1ARC Prize–95.5%
ARC-AGI-2ARC Prize–89.6%
ARC-AGI-3ARC Prize–23.0%
CritPtArtificial Analysis16.9%30.9%
CritPt v2 hard subset (AA)Artificial Analysis–66.5%
MysteryMechanismVals AI–30.2%
Chess PuzzlesEpoch AI Benchmarking Hub–56.0%
Mystery Game PuzzlesEpoch AI Benchmarking Hub–56.0%
LMCAEpoch AI Benchmarking Hub–59.1%
DTBenchEpoch AI Benchmarking Hub–97.3%
Coding
SWE-bench Verified (Epoch)Epoch AI Benchmarking Hub74.8%†–
SciCodeSciCode–57.6%
WeirdMLWeirdML77.9%–
FrontierCodeCognition–49.3%
Arena CodingArena (LMArena)–1520
Arena WebDevArena (LMArena)1406†1674
LiveBench 1.0 CodingLiveBench–81.8%
LiveCodeBenchVals AI87.3%–
IOIVals AI53.8%82.6%
Show all 108 benchmarks
MetricPublisherGPT-5.3-Codex (xhigh)GPT-6 Sol (max)
Coding
SWE-bench (Vals)Vals AI78.0%–
Code MigrationVals AI–57.2%
ProgramBenchVals AI–2.0%
Vibe Code Bench v1.1Vals AI61.8%87.8%
ALE-BenchEpoch AI Benchmarking Hub1655.22462
Terminal-Bench 4.0 (AA)Artificial Analysis–43.9%
GameBench 2 OverallDuelLab GameBench 2–72.9†
GameBench 2 by reasoning settingDuelLab GameBench 2–79.3†
Design Arena WebsiteDesign Arena1159†1285†
FrontierCode 2.0 (AA)Artificial Analysis–35.6%
Agents & tools
Terminal-BenchTerminal-Bench78.4%†50.3%
APEX-AgentsMercor–54.3%
Arena AgentArena (LMArena)–7
LiveBench Agentic CodingLiveBench–52.9%
Terminal-Bench HardArtificial Analysis53.0%–
τ²-Bench Telecom (AA)Artificial Analysis86.0%–
Terminal-Bench 2.1 (Vals)Vals AI–83.2%
HiL-BenchScale AI SEAL4.3%†–
ITBench SRE (AA)Artificial Analysis–49.4%
CyberBenchVals AI–78.0%
Finance Agent v2Vals AI–49.0%
Harvey's Legal Agent Benchmark v1Vals AI–1.7%
Legal Research BenchVals AI–28.9%
SREBenchVals AI–30.5%
Tax Agent BenchVals AI–15.0%
Terminal-Bench 2.0 (Vals)Vals AI64.0%†–
Terminal-Bench 4.0 (Vals)Vals AI–44.4%
Terminal-Bench ScienceVals AI–30.0%
Arena SearchArena (LMArena)–1229
METR Time HorizonsMETR74.5%†–
Vending-Bench 2Andon Labs5940.1†14427.9†
AutomationBenchArtificial Analysis–61.6%
GDP.pdf (AA)Artificial Analysis–25.2%
Harvey LAB-AA v1.1Harvey–3.6%
AA-Briefcase v1.1Artificial Analysis8681476
Design Arena AgenticDesign Arena1014†1212†
Terminal-Bench-Science 0.1 (AA)Artificial Analysis–30.0%
CWE-Bench (AA)Artificial Analysis–64.2%
DeepSec-Bench (AA)Artificial Analysis–46.3%
CyberGym end-to-end (AA)Artificial Analysis–0.0%
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub–89.8%
FrontierMath Tier 4Epoch AI Benchmarking Hub–90.0%
OTIS Mock AIMEEpoch AI Benchmarking Hub–100.0%
ProofBenchVals AI–83.0%†
LiveBench MathematicsLiveBench–96.4%
Arena MathsArena (LMArena)–1440
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub–60.7%
LiveBench 1.0 Data AnalysisLiveBench–81.2%
AA-Omniscience v1.1Artificial Analysis–21.4
PRBench LegalScale AI SEAL–38.6%†
BioMysteryBenchVals AI–74.8%
Excel Modeling BenchmarkVals AI–71.5%
MedCodeVals AI–47.1%
MedScribeVals AI–82.0%
Public Benefits Bench v1.1Vals AI–56.6%
EBR-benchEpoch AI Benchmarking Hub–53.3%
GDP.pdfEpoch AI Benchmarking Hub–26.4%
AA-Omniscience v1.1: accuracyArtificial Analysis–51.1%
AA-Omniscience v1.1: non-hallucinationArtificial Analysis–39.1%
HealthBench Professional (AA)OpenAI–62.3%
Instruction following
LiveBench LanguageLiveBench–85.3%
LiveBench Instruction FollowingLiveBench–68.6%
IFBenchArtificial Analysis75.4%–
Arena Instruction FollowingArena (LMArena)–1448
Human preference
Arena TextArena (LMArena)–1457
Arena Creative WritingArena (LMArena)–1430
Arena Multi-turnArena (LMArena)–1466
Arena Longer QueriesArena (LMArena)–1466
Multimodal
Arena VisionArena (LMArena)–1232
MMMU-ProArtificial Analysis78.5%83.0%
Blueprint-Bench 2Epoch AI Benchmarking Hub–36.9%†
AA-3DArtificial Analysis–1131
Long context
AA-LCR v1.1Artificial Analysis83.3%83.7%
MLCRArtificial Analysis–33.9%
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub–164.1†
LiveBench 1.0LiveBench–79.3%
AA Intelligence Index v5.0Artificial Analysis–44.2
AA Intelligence Index v4.3.2Artificial Analysis32.547.6
AA Progress Index v1Artificial Analysis301.3334
Vals RSI IndexVals AI–28.1%
Vals Science IndexVals AI–45.0%
AA Cyber IndexArtificial Analysis–36.8
Safety & honesty
FORTRESSScale AI SEAL–13.5%†

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 Sol (max): BenchLeader Index 63.5 → 62.9.
  • GPT-6 Sol (max): 2 score revisions.
  • GPT-6 Sol (max): 1 score revision.
  • GPT-6 Sol (max): 1 score revision.
  • GPT-6 Sol (max): 6 new results (AA Intelligence Index v5.0, AA-Omniscience v1.1, CritPt v2 hard subset (AA)…).
  • GPT-6 Sol (max): 1 score revision.
  • GPT-5.3-Codex (xhigh): 1 new result (AA-Briefcase v1.1).
  • GPT-6 Sol (max): 1 score revision.
  • GPT-6 Sol (max): BenchLeader Index 64.1 → 63.5.
  • GPT-5.3-Codex (xhigh): 1 new result (AA Progress Index v1).

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

GPT-5.3-Codex vs GPT-6 Sol: questions

Is GPT-5.3-Codex better than GPT-6 Sol?
GPT-5.3-Codex (xhigh) and GPT-6 Sol (max) are neck and neck on quality (62.9 vs 62.9, within the ±7.6 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 9 Nov 2026, so check the category scores for your use.
GPT-5.3-Codex vs GPT-6 Sol: which is cheaper, and will that change?
GPT-6 Sol is cheaper today: $4.00 against $4.81 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
Is GPT-5.3-Codex or GPT-6 Sol better for coding?
GPT-6 Sol scores higher in coding (67 vs 61 on the category index, where 50 is average). On IOI, the top shared coding benchmark, it is 53.8% for GPT-5.3-Codex against 82.6% for GPT-6 Sol.
Which is faster, GPT-5.3-Codex or GPT-6 Sol?
GPT-6 Sol streams ~1.5× faster (121 vs 77 output tokens per second, Artificial Analysis 7-day median).
Is GPT-5.3-Codex or GPT-6 Sol better for agents and tool use?
GPT-5.3-Codex scores higher in agentic tasks (80 vs 60 on the category index, where 50 is average).
More questions (4)
Which is better for long documents?
They are level on long-context benchmarks (66 vs 67). GPT-6 Sol accepts more context: 1,050,000 against 400,000 tokens for GPT-5.3-Codex.
Which has lower latency?
GPT-5.3-Codex answers first: 42.9 s against 72.1 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-5.3-Codex vs GPT-6 Sol?
Across the 9 benchmarks both have, GPT-5.3-Codex leads 0, GPT-6 Sol leads 9.
When was GPT-6 Sol released?
GPT-6 Sol was released on 22 Sep 2026.