Data as of October 17, 2026 · How the score is built
Released Dec 11, 2025400K context
GPT-5.2
Decision readingGPT-5.2 scores 59.9 out of 100 and ranks #56 of 224. This profile shows 31 source-displayable benchmark rows; its strongest eligible category is Multimodal & Grounded at #22. API pricing is $1.75 input and $14 output per million tokens.
Released Dec 11, 2025 — see all recent releases
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.
Capability
59.9/100
field median 49.6#56 of 224 ranked models
Public
#56of 224
Verified #38 of 88
Price
$1.75input / $14 output
input median $0.75blended $7.88
Speed
80tok/s
field median 92 tok/sFirst token 81.31 s
Context
400Ktokens
field median 256,000Reported for this model; direct source link not stored
Strongest published evidence
Multimodal & Grounded ranks #22. Particularly strong for screenshots, documents, charts, and grounded multimodal workflows.
Validate before choosing
31 published rows leave some tracked benchmark slots empty. Coding is its lowest eligible category at #73.
Source-linked · 31 displayable benchmark rows
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 #58 of 128Percentile 55thWeight 22%4 benchmarksVerified | 44.4 | 4 benchmarks | Verified | |||
| CodingRank #73 of 150Percentile 52ndWeight 20%3 benchmarksVerified | 36.8 | 3 benchmarks | Verified | |||
| ReasoningRank Not rankedWeight 17%2 benchmarksVerified | 64.3 | 2 benchmarks | Verified | |||
| MultimodalRank #22 of 54Percentile 60thWeight 12%18 benchmarksMixed sources | 75.9 | 18 benchmarks | Mixed sources | |||
| KnowledgeRank #50 of 184Percentile 73rdWeight 12%1 benchmarkReported | 59.7 | 1 benchmark | Reported | |||
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MathRank Not rankedWeight 5%3 benchmarksVerified | 71.1 | 3 benchmarks | Verified |
31 of 681 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow 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
- Coding3/3 verified
- Reasoning2/2 verified
- Multimodal1/18 verified
- Knowledge0/1 verified
- MultilingualNot measured
- Inst. FollowingNot measured
- Math3/3 verified
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-5.2 category percentile values
- Agentic55th percentile
- Coding52nd percentile
- ReasoningNot eligible
- Multimodal60th percentile
- Knowledge73rd percentile
- MultilingualNot eligible
- Instruction followingNot eligible
- MathNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#58/128
- Coding#73/150
- ReasoningNot ranked
- Multimodal#22/54
- Knowledge#50/184
- MultilingualNot ranked
- Inst. FollowingNot ranked
- MathNot ranked
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.
Coding3 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| SWE-bench Pro | Score55.6% | Versus best verified row Best verified: Claude Opus 5.5 · 89.9% | Gap34.3 behind | Weight26% ref. weight | Provider exact |
| SWE-bench VerifiedSoftware Engineering Benchmark Verified | Score80% | Versus best verified row Best verified: Claude Opus 5 · 96% | Gap16 behind | WeightDisplay only | Provider exact |
| Vibe Code BenchVibe Code Bench v1.1 | Score53.50% | Versus best verified row Best verified: Gemini 4 Argon · 91.90% | Gap38.4 behind | WeightDisplay only | Benchmark exact |
Agentic4 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| BrowseComp | Score65.8% | Versus best verified row Best verified: Atria Dawn Preview · 92.5% | Gap26.7 behind | Weight8% ref. weight | Provider exact |
| OSWorld-Verified | Score47.3% | Versus best verified row Best verified: Qwen3.8 Max · 86.1% | Gap38.8 behind | Weight7% ref. weight | Provider exact |
| JobBench | Score34.3% | Versus best verified row Best verified: Muse Wonder Full · 75.3% | Gap41 behind | Weight6% ref. weight | Benchmark exact |
| Gert LabsGert Labs Composite Game Benchmark | Score46.54% | Versus best verified row Best verified: Claude Opus 4.8 · 72.97% | Gap26.4 behind | WeightDisplay only | Benchmark exact |
Reasoning2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| ARC-AGI-2Abstraction and Reasoning Corpus for AGI v2 | Score52.9% | Versus best verified row Best verified: GPT-6 Astra · 95% | Gap42.1 behind | WeightWeighted 25% | Provider exact |
| ARC-AGI-1ARC-AGI-1 Semi-Private Evaluation | Score86.17% | Versus best verified row Best verified: GPT-6 Astra · 98.50% | Gap12.3 behind | WeightDisplay only | Benchmark exact |
Multimodal18 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MMMU-ProMassive Multi-discipline Multimodal Understanding Pro | Score79.5% | Versus best verified row Best verified: Gemini 3.5 Flash · 83.6% | Gap4.1 behind | WeightWeighted 40% | Provider exact |
| CharXivCharXiv Reasoning | Score82.1% | Versus best verified row Best verified: Qwen3.8 Max · 93.5% | Gap11.4 behind | WeightWeighted 20% | Secondary exact |
| MMMUMassive Multi-discipline Multimodal Understanding | Score86.7% | Versus best verified row Best verified: Qwen3.5 397B · 85.0% | Gap1.7 behind | WeightDisplay only | Secondary exact |
| RealWorldQA | Score83.3% | Versus best verified row Best verified: Qwen3.8-Flash-Next · 88.5% | Gap5.2 behind | WeightDisplay only | Secondary exact |
| OmniDocBench 1.5 | Score85.7% | Versus best verified row Best verified: Qwen3.8 Max · 92.1% | Gap6.4 behind | WeightDisplay only | Secondary exact |
| Video-MME (with subtitle)Video-MME with subtitle | Score86.0% | Versus best verified row Best verified: Qwen3.8 Max · 90.4% | Gap4.4 behind | WeightDisplay only | Secondary exact |
| Video-MME (w/o subtitle)Video-MME without subtitle | Score85.8% | Versus best verified row Best verified: Qwen3.5 397B · 83.7% | Gap2.1 behind | WeightDisplay only | Secondary exact |
| MathVision | Score83.0% | Versus best verified row Best verified: Qwen3.8 Max · 95.2% | Gap12.2 behind | WeightDisplay only | Secondary exact |
| We-Math | Score79.0% | Versus best verified row Best verified: Qwen3.5 397B · 87.9% | Gap8.9 behind | WeightDisplay only | Secondary exact |
| DynaMath | Score86.8% | Versus best verified row Best verified: Qwen3.5 397B · 86.3% | Gap0.5 behind | WeightDisplay only | Secondary exact |
| SimpleVQA | Score55.8% | Versus best verified row Best verified: Qwen3.7 Plus · 81.7% | Gap25.9 behind | WeightDisplay only | Secondary exact |
| CC-OCR | Score70.3% | Versus best verified row Best verified: Qwen3.5 397B · 82.0% | Gap11.7 behind | WeightDisplay only | Secondary exact |
| AI2D_TESTAI2D test split | Score92.2% | Versus best verified row Best verified: Qwen3.5 397B · 93.9% | Gap1.7 behind | WeightDisplay only | Secondary exact |
| CountBench | Score91.9% | Versus best verified row Best verified: Qwen3.6-27B · 97.8% | Gap5.9 behind | WeightDisplay only | Secondary exact |
| ERQA | Score59.8% | Versus best verified row Best verified: Qwen3.8 Max · 77.8% | Gap18 behind | WeightDisplay only | Secondary exact |
| VideoMMMU | Score85.9% | Versus best verified row Best verified: Qwen3.8 Max · 88.7% | Gap2.8 behind | WeightDisplay only | Secondary exact |
| MLVU (M-Avg)MLVU mean average | Score85.6% | Versus best verified row Best verified: Qwen3.8 Max · 90.8% | Gap5.2 behind | WeightDisplay only | Secondary exact |
| V* | Score75.9% | Versus best verified row Best verified: Qwen3.6 Plus · 96.9% | Gap21 behind | WeightDisplay only | Secondary exact |
Knowledge1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| GPQAGraduate-Level Google-Proof Q&A | Score92.4% | Versus best verified row Best verified: GPT-6 Astra · 96% | Gap3.6 behind | Weight3% ref. weight | Secondary exact |
Math3 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)FrontierMath v2 Tiers 1-3 | Score67.400% | Versus best verified row Best verified: GPT-6 Astra · 93.684% | Gap26.3 behind | WeightWeighted 30% | Benchmark exact |
| FrontierMath v2 (Tier 4)FrontierMath v2 Tier 4 | Score31.700% | Versus best verified row Best verified: GPT-6.1 Sol · 100.000% | Gap68.3 behind | WeightWeighted 10% | Benchmark exact |
| AIME 2025American Invitational Mathematics Examination 2025 | Score100% | Versus best verified row Best verified: GPT-5.2 · 100% | GapBest verified | WeightDisplay only | Provider exact |
Bars run 0–100; the dark tick marks the best source-verified value
All 31 rowsWhat 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.
GPT-5.2 · 59.9 score · $7.88 blended per million tokens
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Horizontal: blended price per million tokens, log scale · Vertical: public score
Published price history
This chart appears only when at least two dated first-party price records exist for the exact model. It shows rate changes, not an inferred cost trend.
3 dated first-party price records. The newest record lists $14 per million tokens.
Lineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
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
- Not published
- Context window
- 400K
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not disclosed by the provider
- Availability
- Not sourced yet
- Cloud regions
- Not tracked yet
- Lifecycle
- Established
- 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
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-5.2 ranks #56 of 224 on the public leaderboard with a score of 59.86/100. Its source-verified position is #38 of 88.
GPT-5.2 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-5.2 sits in the GPT-5.2 family with GPT-5.2 Instant, GPT-5.2 Pro. 31 of 681 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Multimodal & Grounded at #22, while its lowest eligible position is Coding at #73. particularly strong for screenshots, documents, charts, and grounded multimodal workflows.
Last updated October 17, 2026. Runtime fields remain blank until a sourced snapshot exists.
Questions
How does GPT-5.2 perform overall in AI benchmarks?
GPT-5.2 ranks #56 out of 224 models on the public BenchAlign leaderboard, with a score of 59.86/100. Its evidence status is Supported, and this profile shows 31 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is GPT-5.2 good for knowledge and understanding?
GPT-5.2 ranks #50 out of 184 eligible models for knowledge and understanding, with a public category score of 59.7/100. 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-5.2 good for coding and programming?
GPT-5.2 ranks #73 out of 150 eligible models for coding and programming, with a public category score of 36.8/100. 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-5.2 good for mathematics?
GPT-5.2 has source-displayable benchmark coverage for mathematics, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is GPT-5.2 good for reasoning and logic?
GPT-5.2 has source-displayable benchmark coverage for reasoning and logic, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is GPT-5.2 good for agentic tool use and computer tasks?
GPT-5.2 ranks #58 out of 128 eligible models for agentic tool use and computer tasks, with a public category score of 44.4/100. 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-5.2 good for multimodal and grounded tasks?
GPT-5.2 ranks #22 out of 54 eligible models for multimodal and grounded tasks, with a public category score of 75.9/100. 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-5.2?
GPT-5.2 belongs to the GPT-5.2 family. Related tracked variants include GPT-5.2 Instant, GPT-5.2 Pro. 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-5.2 have full benchmark coverage on BenchLM?
No. GPT-5.2 currently has 43 source-displayable rows across 681 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-5.2?
GPT-5.2 has a reported context window of 400K in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.