Capability
65.7/100
field median 59.1
#40 of 230 ranked models
GPT-5.3 Codex
Released Feb 5, 2026 — see all recent releases
Decision reading
GPT-5.3 Codex scores 65.7 out of 100 and ranks #40 of 230. This profile shows 8 source-displayable benchmark rows; its strongest eligible category is Agentic at #21. API pricing is $1.75 input and $14 output per million tokens.
Data as of September 2, 2026 · How the score is built
Strongest published evidence
Agentic ranks #21. Particularly useful for coding agents, browser research, and computer-use workflows.
Validate before choosing
8 published rows leave some tracked benchmark slots empty. Coding is its lowest eligible category at #25.
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Price
$1.75input / $14 output
input median $1
blended $7.88
Speed
118tok/s
field median 90 tok/s
First token 63.6 s
Context
400Ktokens
field median 256,000
Maximum output length is tracked separately
Capability shape
Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.
GPT-5.3 Codex category percentile values
- Agentic86th percentile
- Coding84th percentile
- ReasoningNot eligible
- KnowledgeNot eligible
- MathNot eligible
- MultilingualNot eligible
- MultimodalNot eligible
- Instruction followingNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#21/143
- Coding#25/148
- ReasoningNot ranked
- KnowledgeNot ranked
- MathNot ranked
- MultilingualNot ranked
- MultimodalNot ranked
- Inst. FollowingNot ranked
Top decileTop quartileMid-fieldNot eligible
What it costs to get this score
Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Current modelGPT-5.3 Codex · 65.7 score · $7.88 blended per million tokens
Horizontal: blended price per million tokens, log scale · Vertical: public score
How much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic4/4 verified
- Coding4/4 verified
- ReasoningNot measured
- KnowledgeNot measured
- MathNot measured
- MultilingualNot measured
- MultimodalNot measured
- Inst. FollowingNot measured
Verified sourceProvisionalNot measured
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- gpt-5.3-codexOpenAI GPT-5.3 Codex model documentation
- Context window
- 400KOpenAI GPT-5.3 Codex model documentation
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- text, imageOpenAI model catalog
- Output modalities
- textOpenAI model catalog
- Parameters
- Not disclosed by the provider
- Availability
- OpenAI Responses APIOpenAI model catalog
- Cloud regions
- Not tracked yet
- Lifecycle
- activeOpenAI GPT-5.3 Codex model documentation
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing record
- Self-host
- Weights are not published
- Rate limits
- Not tracked yet
Category score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #21 of 143Percentile 86thWeight 22%4 benchmarksVerified | 61.2 | #21 of 143 | 86th | 22% | 4 benchmarks | Verified |
| CodingRank #25 of 148Percentile 84thWeight 20%4 benchmarksVerified | 63.7 | #25 of 148 | 84th | 20% | 4 benchmarks | Verified |
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | Not ranked | Not available | 17% | 0 benchmarks | Not measured |
| KnowledgeWeight 12%0 benchmarksNot measured | Not measured | Not ranked | Not available | 12% | 0 benchmarks | Not measured |
| MathWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | Not ranked | Not available | 12% | 0 benchmarks | Not measured |
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
Benchmark ledger
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Coding4 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| SWE-Rebench | Score58.2% | Versus best verified row Best verified: Claude Opus 4.6 · 65.3% | Gap7.1 behind | WeightWeighted 20% | Benchmark exact |
| SWE-bench VerifiedSoftware Engineering Benchmark Verified | Score85% | Versus best verified row Best verified: Claude Opus 5 · 96% | Gap11 behind | WeightWeighted 16% | Provider exact |
| SWE-bench Pro | Score56.8% | Versus best verified row Best verified: Claude Fable 5.1 · 81.2% | Gap24.4 behind | WeightWeighted 10% | Provider exact |
| Vibe Code BenchVibe Code Bench v1.1 | Score61.77% | Versus best verified row Best verified: Claude Opus 4.7 · 71.00% | Gap9.2 behind | WeightDisplay only | Benchmark exact |
Agentic4 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 2.0 | Score77.3% | Versus best verified row Best verified: GPT-5.6 Sol · 91.9% | Gap14.6 behind | WeightWeighted 38% | Provider exact |
| OSWorld-Verified | Score64.7% | Versus best verified row Best verified: Qwen3.8 Max · 86.1% | Gap21.4 behind | WeightWeighted 34% | Provider exact |
| Gert LabsGert Labs Composite Game Benchmark | Score57.47% | Versus best verified row Best verified: Claude Opus 4.8 · 72.97% | Gap15.5 behind | WeightDisplay only | Benchmark exact |
| JobBench | Score33.7% | Versus best verified row Best verified: Muse Spark 1.3 · 64.9% | Gap31.2 behind | WeightDisplay only | Benchmark exact |
Lineage
The sequence follows explicit supersedes links. A successor's displayed score stays at least 0.1 points above its predecessor; raw benchmark rows do not move. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Feb 5, 2026 · you are here
GPT-5.3 CodexScore 65.7 · $1.75 / $14
Base entry
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
GPT-5.3 Codex ranks #40 of 230 on the public leaderboard with a score of 65.72/100. Its source-verified position is #26 of 105.
GPT-5.3 Codex is a proprietary model with a 400K context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
GPT-5.3 Codex sits in the GPT-5.3 Codex family with GPT-5.3-Codex-Spark. 8 of 416 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Agentic at #21, while its lowest eligible position is Coding at #25. particularly useful for coding agents, browser research, and computer-use workflows.
Radar
Full release historyGPT-5.3 Codex release history
GPT-5.3-Codex released
OpenAI · Model release
Source confirmed
Radar confirmed these at the source. Already tracking GPT-5.3 Codex? See the free Radar Brief for what changes next.
Frequently asked questions
How does GPT-5.3 Codex perform overall in AI benchmarks?
GPT-5.3 Codex ranks #40 out of 230 models on the public BenchAlign leaderboard, with a score of 65.72/100. Its evidence status is Supported, and this profile shows 8 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is GPT-5.3 Codex good for coding and programming?
GPT-5.3 Codex ranks #25 out of 148 eligible models for coding and programming, with a public category score of 63.7/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is GPT-5.3 Codex good for agentic tool use and computer tasks?
GPT-5.3 Codex ranks #21 out of 143 eligible models for agentic tool use and computer tasks, with a public category score of 61.2/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Which sibling models are related to GPT-5.3 Codex?
GPT-5.3 Codex belongs to the GPT-5.3 Codex family. Related tracked variants include GPT-5.3-Codex-Spark. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.
Does GPT-5.3 Codex have full benchmark coverage on BenchLM?
No. GPT-5.3 Codex currently has 21 source-displayable rows across 416 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of GPT-5.3 Codex?
GPT-5.3 Codex has a documented context window of 400K. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.
Compare GPT-5.3 Codex with every tracked model409 comparisons
Last updated September 2, 2026. Runtime fields remain blank until a sourced snapshot exists.
Watch GPT-5.3 Codex in the weekly brief
Get one weekly email when material rank, price, availability, or benchmark evidence changes are worth revisiting.
Read a sample issueJoin 2,000+ readers.