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Gemini 3 Pro vs GPT-5.3-Codex

Full profiles: Gemini 3 Pro (Google) and GPT-5.3-Codex (OpenAI): every benchmark, price and rank.

Updated · Data from 14 sources

As of 29 Oct 2026, Gemini 3 Pro and GPT-5.3-Codex are neck and neck on quality (60.2 vs 62.9 on the BenchLeader Index, inside the ±7.7 margin). Choose Gemini 3 Pro for multimodal (66 vs 61); choose GPT-5.3-Codex for agents & tools (80 vs 62), instruction following (74 vs 60), and coding (61 vs 58).

Key facts (as of 29 Oct 2026)

  • Gemini 3 Pro scores 60.2 on the BenchLeader Index and GPT-5.3-Codex scores 62.9 (BenchLeader, 29 Oct 2026).
  • GPT-5.3-Codex costs $4.81 per 1M tokens blended (list price, 29 Oct 2026).
  • Of the 3 benchmarks both models have, GPT-5.3-Codex leads 3 (BenchLeader, 29 Oct 2026).
Gemini 3 Pro benchmarks Google GPT-5.3-Codex benchmarks xhigh OpenAIOpen in the comparison tool

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-5.3-Codex61 vs 58 category score; LiveCodeBench 87.3% vs 86.4%Medium
Agents & tool useGPT-5.3-Codex80 vs 62 category scoreHigh
Images and other mediaGemini 3 Pro66 vs 61 category scoreMedium
Following instructionsGPT-5.3-Codex74 vs 60 category scoreHigh
Chat quality (human preference)–Only Gemini 3 Pro has an Arena rating (68 category score)Not comparable
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • Gemini 3 Pro and GPT-5.3-Codex (xhigh) are neck and neck on quality (60.2 vs 62.9, within the ±7.7 margin).
  • Gemini 3 Pro is stronger in human preference, knowledge, maths, multimodal, reasoning.
  • GPT-5.3-Codex (xhigh) is stronger in agents & tools, coding, instruction following, long context.

At a glance

SpecGemini 3 ProGPT-5.3-Codex
DeveloperGoogleOpenAI
Released18 Nov 20255 Feb 2026
Context window (tokens)–400,000
Compared atGemini 3 ProGPT-5.3-Codex (xhigh)
Open weightsNoNo
Price in / out / cached input per 1M–$1.75 / $14.00 / $0.175

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.

CategoryGemini 3 ProGPT-5.3-Codex (xhigh)Leader
Reasoning65.6–not comparable
Coding57.860.9GPT-5.3-Codex
Agents & tools61.680.0GPT-5.3-Codex
Maths54.2–not comparable
Knowledge55.9–not comparable
Instruction following59.973.5GPT-5.3-Codex
Human preference67.7–not comparable
Multimodal65.661.2Gemini 3 Pro
Long context–66.6not comparable

Where sources disagree

Across the 3 benchmarks both have, Gemini 3 Pro leads 0, GPT-5.3-Codex leads 3.

Overall indexGemini 3 ProGPT-5.3-Codex (xhigh)Leader
BenchLeader Index60.262.9neck 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; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.

MeasureGemini 3 ProGPT-5.3-Codex (xhigh)
Blended price per 1M tokens–$4.81
Input / output per 1M– / –$1.75 / $14.00
Cached input per 1M–$0.175
Price per task: chat reply–$0.0049
Price per task: summarize a 30-page report–$0.029
Price per task: code edit–$0.032
Price per task: agentic coding session–$0.161
Price per task: structured extraction–$0.0063
Output speed–80 tok/s
Time to first answer–54.4 s
Time to a complete answer–60.6 s

Each model is compared at its best-ranked reasoning-effort setting. Gemini 3 Pro scores 60.2; Gemini 3 Pro (high) scores 60.1. GPT-5.3-Codex (xhigh) scores 62.9 and takes 54 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

102 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.

MetricPublisherGemini 3 ProGPT-5.3-Codex (xhigh)
BenchLeader IndexBenchLeader60.262.9
Agents & tools scoreBenchLeader61.680.0
Coding scoreBenchLeader57.860.9
Human preference scoreBenchLeader67.7–
Instruction following scoreBenchLeader59.973.5
Knowledge scoreBenchLeader55.9–
Maths scoreBenchLeader54.2–
Multimodal scoreBenchLeader65.661.2
Reasoning scoreBenchLeader65.6–
Long context scoreBenchLeader–66.6
Blended price $/MBenchLeader–$4.81
Output speedBenchLeader–80 tok/s
Time to first answerBenchLeader–54.4 s
Context windowBenchLeader–400,000 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub92.6%–
Humanity's Last ExamScale AI / CAIS37.5%–
SimpleBenchSimpleBench76.4%–
Arena Hard PromptsArena (LMArena)1502–
GPQA Diamond (AA)Artificial Analysis90.8%†91.5%
Humanity's Last Exam (AA)Artificial Analysis39.7%†42.5%
GPQA Diamond (Vals)Vals AI91.7%†–
Kagi LLM BenchmarkKagi LLM Benchmark80.1%–
GPQA Diamond (HELM)HELM Capabilities80.3%–
ARC-AGI-1ARC Prize75.0%–
ARC-AGI-2ARC Prize54.0%–
CritPtArtificial Analysis9.1%†16.9%
SciPredictScale AI SEAL25.3%–
CL-benchEpoch AI Benchmarking Hub15.8%–
ForecastBenchForecastBench65.2%–
Coding
SWE-bench Verified (Epoch)Epoch AI Benchmarking Hub72.9%74.8%†
WeirdMLWeirdML69.9%77.9%
GSO-BenchGSO-Bench18.6%–
Arena CodingArena (LMArena)1517–
Arena WebDevArena (LMArena)14401407†
LiveCodeBenchVals AI86.4%87.3%
IOIVals AI–53.8%
SWE-bench (Vals)Vals AI76.4%†78.0%
SWE-Bench ProScale AI SEAL43.3%–
SWE-bench Verified (bash only)SWE-bench74.2%–
Show all 102 benchmarks
MetricPublisherGemini 3 ProGPT-5.3-Codex (xhigh)
Coding
SWE-bench Verified (any scaffold)SWE-bench77.4%–
Vibe Code Bench v1.1Vals AI14.3%†61.8%
SWE-Bench Pro (private)Scale AI SEAL43.3%–
ALE-BenchEpoch AI Benchmarking Hub1176.81655.2
AlgoTuneAlgoTune1.8–
LiveCodeBench (AA)Artificial Analysis91.8%†–
Agents & tools
Terminal-BenchTerminal-Bench69.4%78.4%†
GDPvalOpenAI40.3%–
Remote Labor IndexScale AI / CAIS1.3%–
Terminal-Bench HardArtificial Analysis41.7%†53.0%
τ²-Bench Telecom (AA)Artificial Analysis87.1%†86.0%
MCP AtlasScale AI SEAL70.3%–
HiL-BenchScale AI SEAL–4.3%†
BFCL OverallBerkeley Function Calling Leaderboard72.5%–
τ²-benchτ²-bench82.5%†–
τ³-bench Bankingτ²-bench18.0%†–
Poker AgentVals AI1078.9%–
Terminal-Bench 2.0 (Vals)Vals AI55.1%†64.0%†
BALROGBALROG58.1%–
DeepResearch BenchDeepResearch Bench46.3%†–
METR Time HorizonsMETR71.0%74.5%†
Vending-Bench 2Andon Labs5478.25940.1†
AA-Briefcase v1.1Artificial Analysis–868
Maths
OTIS Mock AIMEEpoch AI Benchmarking Hub91.4%–
ProofBenchVals AI20.0%–
AIME (Vals)Vals AI96.7%†–
MGSMVals AI93.9%†–
AIME 2026MathArena91.7%–
HMMT February 2026MathArena86.4%–
MathArena ApexMathArena23.4%–
Omni-MATH (HELM)HELM Capabilities55.6%–
MATH 500Vals AI96.4%†–
Arena MathsArena (LMArena)1477–
Knowledge
MMLU-ProVals AI90.1%–
LegalBenchVals AI87.0%†–
CorpFinVals AI63.7%†–
TaxEvalVals AI72.6%†–
MedQAVals AI96.0%†–
PRBench FinanceScale AI SEAL39.2%–
PRBench LegalScale AI SEAL40.6%–
MultiNRCScale AI SEAL59.0%–
MMLU-Pro (HELM)HELM Capabilities90.3%–
CaseLaw v2Vals AI53.1%†–
MedCodeVals AI52.2%†–
MedScribeVals AI72.0%†–
Global-MMLU-Lite (AA)Artificial Analysis92.2%†–
Instruction following
IFBenchArtificial Analysis70.4%†75.4%
MultiChallengeScale AI SEAL65.7%–
TutorBenchScale AI SEAL53.7%–
IFEval (HELM)HELM Capabilities87.6%–
WildBench (HELM)HELM Capabilities85.9%–
Arena Instruction FollowingArena (LMArena)1472–
Human preference
Arena TextArena (LMArena)1485–
Arena Creative WritingArena (LMArena)1485–
Arena Multi-turnArena (LMArena)1496–
Arena Longer QueriesArena (LMArena)1490–
Multimodal
Arena VisionArena (LMArena)1305–
MMMU-ProArtificial Analysis80.2%†78.5%
VISTAScale AI SEAL51.5%–
MMMU-Pro (official)MMMU81.0%–
MMMU-Pro (Vals)Vals AI87.5%†–
MortgageTaxVals AI69.1%†–
AudioMCScale AI SEAL54.6%†–
AudioMC (text output)Scale AI SEAL54.6%†–
VTBScale AI SEAL26.9%–
GeoBenchGeoBench84.0%–
VPCTEpoch AI Benchmarking Hub91.0%–
Long context
AA-LCR v1.1Artificial Analysis76.0%†83.3%
Arena DocumentArena (LMArena)1451–
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub153.1157.1†
AA Intelligence Index v4.3.2Artificial Analysis28.0†32.5
AA Progress Index v1Artificial Analysis290.7†301.3
HELM Capabilities meanHELM Capabilities79.9%–
Safety & honesty
FORTRESSScale AI SEAL41.7%–
MASKScale AI SEAL42.6%–
PropensityBenchScale AI SEAL52.9%–
Metadata
AA Openness IndexArtificial Analysis5.6†–

Data as of 2026-10-29. Best configuration of each model; every score links to its source on the model pages.

What changed

  • GPT-5.3-Codex (xhigh): 1 new result (AA-Briefcase v1.1).
  • GPT-5.3-Codex (xhigh): 1 new result (AA Progress Index v1).
  • Gemini 3 Pro: 1 score revision.
  • Gemini 3 Pro: 1 score revision.
  • Gemini 3 Pro: BenchLeader Index 60.9 → 60.4.
  • Gemini 3 Pro: 1 new result (PRBench Legal).
  • Gemini 3 Pro: BenchLeader Index 60.4 → 60.9.
  • Gemini 3 Pro: 1 new result (VTB).
  • Gemini 3 Pro: 2 new results (PRBench Legal, MultiNRC).
  • Gemini 3 Pro: BenchLeader Index 61.0 → 60.4.

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

Gemini 3 Pro vs GPT-5.3-Codex: questions

Is Gemini 3 Pro better than GPT-5.3-Codex?
Gemini 3 Pro and GPT-5.3-Codex (xhigh) are neck and neck on quality (60.2 vs 62.9, within the ±7.7 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 29 Oct 2026, so check the category scores for your use.
Is Gemini 3 Pro or GPT-5.3-Codex better for coding?
GPT-5.3-Codex scores higher in coding (61 vs 58 on the category index, where 50 is average). On LiveCodeBench, the top shared coding benchmark, it is 86.4% for Gemini 3 Pro against 87.3% for GPT-5.3-Codex.
Is Gemini 3 Pro or GPT-5.3-Codex better for agents and tool use?
GPT-5.3-Codex scores higher in agentic tasks (80 vs 62 on the category index, where 50 is average).
Do independent benchmarks agree on Gemini 3 Pro vs GPT-5.3-Codex?
Across the 3 benchmarks both have, Gemini 3 Pro leads 0, GPT-5.3-Codex leads 3.
When was GPT-5.3-Codex released?
GPT-5.3-Codex was released on 5 Feb 2026.