DeepSeek
RankedEnough results for an index.DeepSeek V3.2 (Thinking)
DeepSeek V3.2 (Thinking) is a reasoning model from DeepSeek in the DeepSeek V3.2 family. 10 benchmarks count toward its index, in 4 categories.
IndexAll categories, out of 100.49.4±8.6Median 51.0
CoverageIndex weight that has results.65%
SpeedOutput tokens per second.—Median 67/s
First tokenSeconds to the first output token.—Median 1.3 s
Input / 1MUS dollars per 1M input tokens.$0.55Median $0.60
Output / 1MUS dollars per 1M output tokens.$2.19Median $2.55
ContextMaximum tokens in one request.128KMedian 262K
EloLMArena rating and rank.1420±4 #116Median 1422
Run locally
685.36B parameters- 16-bit
- 1440.3 GB
- 8-bit
- 765.6 GB
- 4-bit
- 437.3 GB
Memory need with a short context. The 4-bit copy needs more than 128 GB. Compare local models
Capabilities
Index per category, out of 100.Results
10 countedBenchmarkThe benchmark name.ResultThe score from the source.PlacePlace among results on this benchmark.
Sources
BenchLMCC BY-NC 4.0Vals AINo licence statedHistory
5 releases23 Oct 202612 Nov 2026
23 Oct 202612 Nov 2026
Questions
- How much does DeepSeek V3.2 (Thinking) cost?
- $0.55 per 1M input tokens, $2.19 per 1M output tokens.
- How good is DeepSeek V3.2 (Thinking)?
- Its index is 49.4 out of 100. That is place 153 of 283 ranked models.
- What is DeepSeek V3.2 (Thinking) best at?
- Knowledge: 51.2 out of 100, place 125 of 268.
- What is the context window of DeepSeek V3.2 (Thinking)?
- 128K tokens.
- Is DeepSeek V3.2 (Thinking) open source?
- Yes. Its weights are published.
- When was DeepSeek V3.2 (Thinking) released?
- December 2025.
Badge
- HTML
<a href="https://inference360.ai/models/deepseek-v3-2-thinking"><img src="https://inference360.ai/badges/deepseek-v3-2-thinking.svg" alt="DeepSeek V3.2 (Thinking) on Inference360: place 153 of 283, index 49.4" height="20"></a>- Markdown
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