DeepSeek V3.2 vs Llama 3.1 405B Instruct
DeepSeek V3.2 (2025) and Llama 3.1 405B Instruct (2024) are compact production models from DeepSeek and AI at Meta. DeepSeek V3.2 ships a 160K-token context window, while Llama 3.1 405B Instruct ships a 128K-token context window. On pricing, DeepSeek V3.2 costs $0.25/1M input tokens versus $2.4/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
DeepSeek V3.2 is ~852% cheaper at $0.25/1M; pay for Llama 3.1 405B Instruct only for provider fit.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-01-01 | 2024-07-23 |
| Context window | 160K | 128K |
| Parameters | 671B | 405B |
| Architecture | decoder only | decoder only |
| License | Open Source | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| Pricing attribute | DeepSeek V3.2 | Llama 3.1 405B Instruct |
|---|---|---|
| Input price | $0.25/1M tokens | $2.4/1M tokens |
| Output price | $0.38/1M tokens | $2.4/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V3.2 | Llama 3.1 405B Instruct |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on code execution: DeepSeek V3.2. Both models share structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, DeepSeek V3.2 lists $0.25/1M input and $0.38/1M output tokens, while Llama 3.1 405B Instruct lists $2.4/1M input and $2.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V3.2 lower by about $2.11 per million blended tokens. Availability is 4 providers versus 11, so concentration risk also matters.
Choose DeepSeek V3.2 when coding workflow support, larger context windows, and lower input-token cost are central to the workload. Choose Llama 3.1 405B Instruct when provider fit and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.
FAQ
Which has a larger context window, DeepSeek V3.2 or Llama 3.1 405B Instruct?
DeepSeek V3.2 supports 160K tokens, while Llama 3.1 405B Instruct supports 128K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, DeepSeek V3.2 or Llama 3.1 405B Instruct?
DeepSeek V3.2 is cheaper on tracked token pricing. DeepSeek V3.2 costs $0.25/1M input and $0.38/1M output tokens. Llama 3.1 405B Instruct costs $2.4/1M input and $2.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V3.2 or Llama 3.1 405B Instruct open source?
DeepSeek V3.2 is listed under Open Source. Llama 3.1 405B Instruct is listed under Open Source. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for structured outputs, DeepSeek V3.2 or Llama 3.1 405B Instruct?
Both DeepSeek V3.2 and Llama 3.1 405B Instruct expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for code execution, DeepSeek V3.2 or Llama 3.1 405B Instruct?
DeepSeek V3.2 has the clearer documented code execution signal in this comparison. If code execution is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run DeepSeek V3.2 and Llama 3.1 405B Instruct?
DeepSeek V3.2 is available on Fireworks AI, NVIDIA NIM, AWS Bedrock, and OpenRouter. Llama 3.1 405B Instruct is available on OctoAI API (Deprecated), Together AI, Fireworks AI, IBM watsonx, and Scale AI GenAI Platform. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.