Model profile
DeepSeek V3.2
Evidence coverage
19 of 321 tracked benchmarks are published. 7 are verified and 12 provisional. 7 of 8 categories are measured.
- Published / tracked
- 19 / 321
- Verified
- 7
- Provisional
- 12
- Categories with evidence
- 7 / 8
Evidence by category
- Agentic4 benchmarksMixed evidence
- Coding3 benchmarksMixed evidence
- Reasoning2 benchmarksReported
- Knowledge6 benchmarksReported
- Math2 benchmarksVerified
- Multilingual0 benchmarksNot measured
- Multimodal1 benchmarkReported
- Inst. Following1 benchmarkReported
DeepSeek V3.2 ranks #82 out of 200 models on the public leaderboard with an overall score of 55.4/100. It also ranks #48 out of 99 on the verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.
DeepSeek V3.2 is a open weight model with a 128K token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.
DeepSeek V3.2 sits inside the DeepSeek V3.2 family alongside DeepSeek V3.2 (Thinking). This profile currently has 19 of 321 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.
Its strongest category is Coding (#59). This performance profile makes it particularly well-suited for software development and code generation tasks.
Peer position
Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.
Range 55.1–55.64
- Hy3TencentCompare#8055.64Hy3 is #80 with a score of 55.64.
- DeepSeek V4 Pro (High)DeepSeekCompare#8155.47DeepSeek V4 Pro (High) is #81 with a score of 55.47.
- DeepSeek V3.2Current modelDeepSeek#8255.4DeepSeek V3.2 is #82 with a score of 55.4.
- Gemini 3.1 ProGoogleCompare#8355.3Gemini 3.1 Pro is #83 with a score of 55.3.
- GPT-5 (medium)OpenAICompare#8455.15GPT-5 (medium) is #84 with a score of 55.15.
- GLM-4.6Z.AICompare#8555.12GLM-4.6 is #85 with a score of 55.12.
- Step 3.5 FlashStepFunCompare#8655.1Step 3.5 Flash is #86 with a score of 55.1.
Category percentile
More
Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.
- Coding52%Eligible cohort rank #59 of 122Category score 51.4
Category evidence
Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank Not rankedWeight 22%4 benchmarksMixed sources | 58.9 | Not ranked | Not available | 22% | 4 benchmarks | Mixed sources |
| CodingRank #59 of 122Percentile 52ndWeight 20%3 benchmarksMixed sources | 51.4 | #59 of 122 | 52nd | 20% | 3 benchmarks | Mixed sources |
| ReasoningRank Not rankedWeight 17%2 benchmarksReported | 49.2 | Not ranked | Not available | 17% | 2 benchmarks | Reported |
| KnowledgeRank Not rankedWeight 12%6 benchmarksReported | 47.2 | Not ranked | Not available | 12% | 6 benchmarks | Reported |
| MathRank Not rankedWeight 5%2 benchmarksVerified | 40.4 | Not ranked | Not available | 5% | 2 benchmarks | Verified |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalRank Not rankedWeight 12%1 benchmarkReported | 65.4 | Not ranked | Not available | 12% | 1 benchmark | Reported |
| Inst. FollowingRank Not rankedWeight 5%1 benchmarkReported | 76.2 | Not ranked | Not available | 5% | 1 benchmark | Reported |
Chatbot Arena performance
Scroll horizontally to inspect confidence intervals and vote counts.
| View | Elo | Confidence interval | Votes |
|---|---|---|---|
| Text Overall | 1425 | ±3.6 | 47,215 |
| Coding | 1470 | ±6.4 | 10,604 |
| Math | 1429 | ±11.0 | 2,987 |
| Instruction Following | 1421 | ±5.9 | 12,905 |
| Creative Writing | 1401 | ±7.8 | 6,674 |
| Multi-turn | 1428 | ±7.2 | 8,256 |
| Hard Prompts | 1447 | ±4.6 | 26,156 |
| Hard Prompts (English) | 1455 | ±6.0 | 12,471 |
| Longer Query | 1442 | ±6.0 | 12,909 |
Benchmark Details
Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.
Agentic4 benchmarks
τ²-Bench Tool-Agent-User Evaluation
Gert Labs Composite Game Benchmark
Coding3 benchmarks
Artificial Analysis SciCode
Reasoning2 benchmarks
Artificial Analysis Long Context Reasoning
Critical Physics Tasks
Knowledge6 benchmarks
Artificial Analysis GPQA Diamond
Artificial Analysis Humanity's Last Exam
Artificial Analysis Omniscience Index
Artificial Analysis Omniscience Accuracy
Artificial Analysis Omniscience Hallucination Rate
Math2 benchmarks
FrontierMath v2 Tiers 1-3
FrontierMath v2 Tier 4
Multimodal1 benchmark
Design Arena Website Elo
Inst. Following1 benchmark
Artificial Analysis IFBench
Frequently Asked Questions
How does DeepSeek V3.2 perform overall in AI benchmarks?
DeepSeek V3.2 has 19 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.
Is DeepSeek V3.2 good for knowledge and understanding?
DeepSeek V3.2 has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Is DeepSeek V3.2 good for coding and programming?
DeepSeek V3.2 ranks #59 out of 122 models in coding and programming benchmarks with an average score of 51.4. There are stronger options in this category.
Is DeepSeek V3.2 good for mathematics?
DeepSeek V3.2 has visible benchmark coverage in mathematics, but BenchLM does not currently assign it a global category rank there.
Is DeepSeek V3.2 good for reasoning and logic?
DeepSeek V3.2 has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.
Is DeepSeek V3.2 good for agentic tool use and computer tasks?
DeepSeek V3.2 has visible benchmark coverage in agentic tool use and computer tasks, but BenchLM does not currently assign it a global category rank there.
Is DeepSeek V3.2 good for multimodal and grounded tasks?
DeepSeek V3.2 has visible benchmark coverage in multimodal and grounded tasks, but BenchLM does not currently assign it a global category rank there.
Is DeepSeek V3.2 good for instruction following?
DeepSeek V3.2 has visible benchmark coverage in instruction following, but BenchLM does not currently assign it a global category rank there.
Is DeepSeek V3.2 open source?
Yes, DeepSeek V3.2 is an open weight model created by DeepSeek, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Which sibling models are related to DeepSeek V3.2?
DeepSeek V3.2 belongs to the DeepSeek V3.2 family. Related variants on BenchLM include DeepSeek V3.2 (Thinking).
Does DeepSeek V3.2 have full benchmark coverage on BenchLM?
Not yet. DeepSeek V3.2 currently has 19 published benchmark scores out of the 321 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.
What is the context window size of DeepSeek V3.2?
DeepSeek V3.2 has a published context window of 128K, which determines how much text it can process in a single interaction.
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