Is Gemini 4 Carbon better than GPT-5.3-Codex?

Gemini 4 Carbon (high) and GPT-5.3-Codex (xhigh) are neck and neck on quality (65.1 vs 62.9, within the ±9.2 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.

Gemini 4 Carbon vs GPT-5.3-Codex: which is cheaper, and will that change?

GPT-5.3-Codex is cheaper today: $4.81 against $8.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.

Is Gemini 4 Carbon or GPT-5.3-Codex better for coding?

Gemini 4 Carbon scores higher in coding (72 vs 61 on the category index, where 50 is average).

Which is faster, Gemini 4 Carbon or GPT-5.3-Codex?

Gemini 4 Carbon streams faster (100 vs 83 output tokens per second, Artificial Analysis 7-day median).

Which is better for long documents?

GPT-5.3-Codex scores higher on long-context benchmarks (67 vs 65). Gemini 4 Carbon accepts more context: 1,000,000 against 400,000 tokens for GPT-5.3-Codex.

Which has lower latency?

GPT-5.3-Codex answers first: 62.2 s against 103.1 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.

When was Gemini 4 Carbon released?

Gemini 4 Carbon was released on 28 Oct 2026.

Gemini 4 Carbon vs GPT-5.3-Codex

Full profiles: Gemini 4 Carbon (Google) and GPT-5.3-Codex (OpenAI): every benchmark, price and rank.

Updated 29 Oct 2026 · Data from 5 sources

As of 29 Oct 2026, Gemini 4 Carbon and GPT-5.3-Codex are neck and neck on quality (65.1 vs 62.9 on the BenchLeader Index, inside the ±9.2 margin), and GPT-5.3-Codex is 1.7× cheaper at $4.81 vs $8.00 per 1M tokens blended. Choose Gemini 4 Carbon for coding (72 vs 61); choose GPT-5.3-Codex for fast first answers (62.2 s vs 103.1 s) and long context (67 vs 65).

Key facts (as of 29 Oct 2026)

Gemini 4 Carbon scores 65.1 on the BenchLeader Index and GPT-5.3-Codex scores 62.9 (BenchLeader, 29 Oct 2026).
Gemini 4 Carbon costs $8.00 per 1M tokens blended (list price, 29 Oct 2026).
GPT-5.3-Codex costs $4.81 per 1M tokens blended (list price, 29 Oct 2026).
Of the 5 benchmarks both models have, Gemini 4 Carbon leads 4 (BenchLeader, 29 Oct 2026).

Gemini 4 Carbon benchmarks high Google

GPT-5.3-Codex benchmarks xhigh OpenAI Open 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 case	Pick	Why	Confidence
Coding	Gemini 4 Carbon	72 vs 61 category score; Vibe Code Bench v1.1 89.1% vs 61.8%	High
Long documents	GPT-5.3-Codex	67 vs 65 category score; AA-LCR v1.1 83.3% vs 79.3%	Medium
Lowest cost	GPT-5.3-Codex	$4.81 vs $8.00 per 1M blended; agentic coding session $0.161 vs $0.320	–
Fastest first answer	GPT-5.3-Codex	62.2 s (GPT-5.3-Codex (xhigh)) vs 103.1 s (Gemini 4 Carbon (high)) 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

Gemini 4 Carbon (high) and GPT-5.3-Codex (xhigh) are neck and neck on quality (65.1 vs 62.9, within the ±9.2 margin).
Gemini 4 Carbon (high) is stronger in coding, knowledge, reasoning.
GPT-5.3-Codex (xhigh) is stronger in long context, agents & tools, instruction following, multimodal.
GPT-5.3-Codex (xhigh) is 1.7× cheaper ($4.81 vs $8.00 per 1M blended).

At a glance

Spec	Gemini 4 Carbon	GPT-5.3-Codex
Developer	Google	OpenAI
Released	28 Oct 2026	5 Feb 2026
Context window (tokens)	1,000,000	400,000
Compared at	Gemini 4 Carbon (high)	GPT-5.3-Codex (xhigh)
Open weights	No	No
Price in / out / cached input per 1M	$4.00 / $20.00 / –	$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.

Category	Gemini 4 Carbon (high)	GPT-5.3-Codex (xhigh)	Leader
Reasoning	78.9	–	not comparable
Coding	71.7	60.9	Gemini 4 Carbon
Agents & tools	–	80.0	not comparable
Knowledge	75.8	–	not comparable
Instruction following	–	73.5	not comparable
Multimodal	–	61.2	not comparable
Long context	64.5	66.6	GPT-5.3-Codex

Where sources disagree

Across the 5 benchmarks both have, Gemini 4 Carbon leads 4, GPT-5.3-Codex leads 1.

Overall index	Gemini 4 Carbon (high)	GPT-5.3-Codex (xhigh)	Leader
BenchLeader Index	65.1	62.9	neck 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.

Measure	Gemini 4 Carbon (high)	GPT-5.3-Codex (xhigh)
Blended price per 1M tokens	$8.00	$4.81
Input / output per 1M	$4.00 / $20.00	$1.75 / $14.00
Cached input per 1M	–	$0.175
Price per task: chat reply	$0.0076	$0.0049
Price per task: summarize a 30-page report	$0.060	$0.029
Price per task: code edit	$0.054	$0.032
Price per task: agentic coding session	$0.320	$0.161
Price per task: structured extraction	$0.012	$0.0063
Cost to run a full benchmark suite	$7.76	–
Output speed	100 tok/s	83 tok/s
Time to first answer	103.1 s	62.2 s
Time to a complete answer	108.1 s	68.3 s

Each model is compared at its best-ranked reasoning-effort setting. Gemini 4 Carbon (high) scores 65.1 and takes 103 s to its first answer token. GPT-5.3-Codex (xhigh) scores 62.9 and takes 62 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

47 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	Gemini 4 Carbon (high)	GPT-5.3-Codex (xhigh)
BenchLeader Index	BenchLeader	65.1	62.9
Coding score	BenchLeader	71.7	60.9
Knowledge score	BenchLeader	75.8	–
Long context score	BenchLeader	64.5	66.6
Reasoning score	BenchLeader	78.9	–
Agents & tools score	BenchLeader	–	80.0
Instruction following score	BenchLeader	–	73.5
Multimodal score	BenchLeader	–	61.2
Blended price $/M	BenchLeader	$8.00	$4.81
Output speed	BenchLeader	100 tok/s	83 tok/s
Time to first answer	BenchLeader	103.1 s	62.2 s
Context window	BenchLeader	1,000,000 tokens	400,000 tokens
Reasoning
GPQA Diamond (AA)	Artificial Analysis	–	91.5%
Humanity's Last Exam (AA)	Artificial Analysis	60.4%	42.5%
HLE-Diamond (AA)	Artificial Analysis	69.1%	–
CritPt	Artificial Analysis	36.0%	16.9%
CritPt v2 hard subset (AA)	Artificial Analysis	63.0%	–
Coding
SWE-bench Verified (Epoch)	Epoch AI Benchmarking Hub	–	74.8%†
SciCode	SciCode	64.2%	–
WeirdML	WeirdML	–	77.9%
Arena WebDev	Arena (LMArena)	–	1407†
LiveCodeBench	Vals AI	–	87.3%
IOI	Vals AI	–	53.8%
SWE-bench (Vals)	Vals AI	–	78.0%
Vibe Code Bench v1.1	Vals AI	89.1%	61.8%
ALE-Bench	Epoch AI Benchmarking Hub	–	1655.2
Terminal-Bench 4.0 (AA)	Artificial Analysis	65.2%	–
FrontierCode 1.1 (AA)	Artificial Analysis	48.5%	–
FrontierCode 2.0 (AA)	Artificial Analysis	40.6%	–
Agents & tools
Terminal-Bench	Terminal-Bench	–	78.4%†
Terminal-Bench Hard	Artificial Analysis	–	53.0%
τ²-Bench Telecom (AA)	Artificial Analysis	–	86.0%
HiL-Bench	Scale AI SEAL	–	4.3%†
Finance Agent v2.1	Vals AI	67.2%	–
Harvey's Legal Agent Benchmark v1.1	Vals AI	17.5%	–
Legal Research Bench	Vals AI	55.8%	–
Tax Agent Bench	Vals AI	48.9%	–

Show all 47 benchmarks

Metric	Publisher	Gemini 4 Carbon (high)	GPT-5.3-Codex (xhigh)
Agents & tools
Terminal-Bench 2.0 (Vals)	Vals AI	–	64.0%†
Terminal-Bench 4.0 (Vals)	Vals AI	63.1%	–
METR Time Horizons	METR	–	74.5%†
Vending-Bench 2	Andon Labs	16484.2†	5940.1†
AutomationBench	Artificial Analysis	77.8%	–
GDP.pdf (AA)	Artificial Analysis	28.4%	–
AA-Briefcase v1.1	Artificial Analysis	1609	–
Terminal-Bench-Science 0.1 (AA)	Artificial Analysis	64.8%	–
Knowledge
AA-Omniscience v1.1	Artificial Analysis	53.5	–
Excel Modeling Benchmark v1.1	Vals AI	76.5%	–
AA-Omniscience v1.1: accuracy	Artificial Analysis	58.3%	–
AA-Omniscience v1.1: non-hallucination	Artificial Analysis	88.6%	–
Instruction following
IFBench	Artificial Analysis	–	75.4%
Multimodal
MMMU-Pro	Artificial Analysis	–	78.5%
Blueprint-Bench 2	Epoch AI Benchmarking Hub	58.6%†	–
Long context
AA-LCR v1.1	Artificial Analysis	79.3%	83.3%
Composite
Epoch Capabilities Index	Epoch AI Benchmarking Hub	–	157.1†
AA Intelligence Index v5.0	Artificial Analysis	59.4	–
AA Intelligence Index v4.3.2	Artificial Analysis	–	32.5
AA Progress Index v1	Artificial Analysis	351.6	301.3
Vals Index	Vals AI	70.4	–
Vals Finance Index	Vals AI	66.3%	–

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

What changed

28 Oct 2026 GPT-5.3-Codex (xhigh): BenchLeader Index 63.4 → 62.9.
28 Oct 2026 GPT-5.3-Codex (xhigh): 1 new result (AA Progress Index v1).
2 Oct 2026 GPT-5.3-Codex (xhigh): BenchLeader Index 64.0 → 63.4.

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