DeepSeek: DeepSeek V3.2
Analysis Summary
DeepSeek V3.2 is a well-rounded release with strong coding performance and high agentic reliability, backed by full benchmark coverage across reasoning, math, and tool-use tasks. It supports both tool use and function calling, making it viable for structured workflows.
For businesses, this profile fits software development support, automated coding pipelines, and multi-step agent tasks where budget matters. Instruction-following and long-context reasoning scores are respectable rather than exceptional, so highly nuanced client-facing writing may need a stronger content-focused model.
Pricing is aggressive for the capability on offer, making it a strong budget alternative to premium coding models where cost efficiency outweighs polish.
Assessed July 19, 2026
Editorial notes
DeepSeek V3.2 delivers strong coding and agentic benchmarks with tool use and function calling, at aggressive pricing and a 163K context window.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
DeepSeek V3.2 delivers strong coding and agentic benchmarks with tool use and function calling, at aggressive pricing and a 163K context window.
Benchmark scores
Magenta = intelligence Ā· Ink = technical/agentic Ā· Cyan = content & long-context Ā· Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
32 Intelligence IndexĀ·44.2 Coding IndexĀ·63.1 Agentic IndexĀ·92 Math Index
How DeepSeek: DeepSeek V3.2 compares
DeepSeek: DeepSeek V3.2 ranks #80 of 393 AI models we track for overall intelligence, #47 of 157 for coding, #45 of 300 for agentic tasks. Its 164K-token context window is larger than 59% of the models we list. At $0.27 per million input tokens it is cheaper than 46% of comparable models.
Dark bar = input Ā· light bar = output, scaled to the priciest peer.
1M tokens ā 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on value. The pulled-in intelligence corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side āPricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.27 | $0.000269 |
| Output | $0.40 | $0.000400 |
What would DeepSeek: DeepSeek V3.2 cost your business?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 612 models ā Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save DeepSeek: DeepSeek V3.2 for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout DeepSeek: DeepSeek V3.2
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism..
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Frequently asked questions about DeepSeek: DeepSeek V3.2
How much does DeepSeek: DeepSeek V3.2 cost?
DeepSeek: DeepSeek V3.2 costs $0.27 per million input tokens and $0.40 per million output tokens.
What is the context window of DeepSeek: DeepSeek V3.2?
DeepSeek: DeepSeek V3.2 has a context window of 163,840 tokens (164K).
Is DeepSeek: DeepSeek V3.2 good for coding?
On our coding benchmark index, DeepSeek: DeepSeek V3.2 ranks #47 of 157 models, placing it in the broader range of the field for code generation and debugging.
What can DeepSeek: DeepSeek V3.2 do?
DeepSeek: DeepSeek V3.2 supports tool use and function calling.
Who created DeepSeek: DeepSeek V3.2?
DeepSeek: DeepSeek V3.2 is developed by DeepSeek and was released on December 1, 2025.
