Scorecard
- Cost effectiveness91
- Coding & agentic84
- Technical capability82
- Reasoning & knowledge78
- Pricing clarity76
- Risk & evidence76
- Developer experience73
- Adoption signal65
- Multimodal & I/O55
- Speed & availability50
Kainotomic evaluation
DeepSeek-V3.2 has unusually strong public coding evidence for an open model. The supplied DeepSeek/Hugging Face materials describe a reasoning-first model aimed at tool-use and agent workflows, and SWE-bench evidence reports 70.00% resolved on SWE-bench Verified from the official leaderboard, while the DeepSeek paper reports 73.1 with robustness runs in the 72-74 range. LiveCodeBench evidence is also strong, with reported V3.2 Thinking scores in the mid-to-high 80s and Speciale near 89. The main weakness is uneven third-party coverage. DeepSWE/DataCurve was checked but does not list DeepSeek-V3.2, so no score should be inferred there. Terminal-Bench provides relevant agentic evidence, listing Terminus 2 with DeepSeek-V3.2 at 39.6%±2.8 accuracy, which is useful but not dominant. Arena evidence is mixed: broad public preference ranks are mid-pack, with Hard Prompts English rank 80 and score 1455±6 from 12,493 votes. Pricing appears highly cost-effective in Artificial Analysis at $0.28/M input and $0.42/M output tokens with 128k context, but official supplied sources did not clearly establish full pricing or license terms. Artificial Analysis lists speed as N/A, limiting availability scoring. Overall, the model looks strong for coding and agent evaluations, especially where open availability and low token cost matter, but its evidence base is split between provider-reported results, selected benchmark listings, and some missing leaderboard coverage.
Strengths
- Strong SWE-bench Verified evidence: 70.00% official leaderboard result and 73.1 provider-reported result with robustness range of 72-74.
- Strong LiveCodeBench evidence for V3.2 Thinking and Speciale variants.
- Low reported token pricing from Artificial Analysis and 128k context window.
- Official DeepSeek and Hugging Face pages support the model’s positioning for reasoning, coding, tool use, and agent workflows.
Caveats
- DeepSWE/DataCurve was checked but DeepSeek-V3.2 was not listed, so no DeepSWE score is available.
- Artificial Analysis speed is N/A, limiting speed and availability confidence.
- Arena public-preference ranks are mid-tier rather than frontier-leading.
- Some benchmark values are from DeepSeek-authored paper/model-card evidence rather than independent leaderboard entries.