DeepSeek R1 vs Llama 3.1 70B Instruct
DeepSeek R1 (2025) and Llama 3.1 70B Instruct (2024) are frontier reasoning models from DeepSeek and AI at Meta. DeepSeek R1 ships a 128K-token context window, while Llama 3.1 70B Instruct ships a 128K-token context window. On HumanEval, DeepSeek R1 leads by 5.8 pts. On pricing, DeepSeek R1 costs $0.1/1M input tokens versus $0.4/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
DeepSeek R1 is ~300% cheaper at $0.1/1M; pay for Llama 3.1 70B Instruct only for provider fit.
Specs
| Released | 2025-01-20 | 2024-07-23 |
| Context window | 128K | 128K |
| Parameters | 671B, 37B Active | 70B |
| Architecture | decoder only | decoder only |
| License | Open Source | Open Source |
| Knowledge cutoff | - | - |
Pricing and availability
| DeepSeek R1 | Llama 3.1 70B Instruct | |
|---|---|---|
| Input price | $0.1/1M tokens | $0.4/1M tokens |
| Output price | $0.3/1M tokens | $0.4/1M tokens |
| Providers |
Capabilities
| DeepSeek R1 | Llama 3.1 70B Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | DeepSeek R1 | Llama 3.1 70B Instruct |
|---|---|---|
| HumanEval | 89.9 | 84.1 |
Deep dive
On shared benchmark coverage, HumanEval has DeepSeek R1 at 89.9 and Llama 3.1 70B Instruct at 84.1, with DeepSeek R1 ahead by 5.8 points. The largest visible gap is 5.8 points on HumanEval, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on reasoning mode: DeepSeek R1 and code execution: DeepSeek R1. 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 R1 lists $0.1/1M input and $0.3/1M output tokens, while Llama 3.1 70B Instruct lists $0.4/1M input and $0.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek R1 lower by about $0.24 per million blended tokens. Availability is 13 providers versus 11, so concentration risk also matters.
Choose DeepSeek R1 when coding workflow support, lower input-token cost, and broader provider choice are central to the workload. Choose Llama 3.1 70B Instruct when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, DeepSeek R1 or Llama 3.1 70B Instruct?
DeepSeek R1 supports 128K tokens, while Llama 3.1 70B 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 R1 or Llama 3.1 70B Instruct?
DeepSeek R1 is cheaper on tracked token pricing. DeepSeek R1 costs $0.1/1M input and $0.3/1M output tokens. Llama 3.1 70B Instruct costs $0.4/1M input and $0.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek R1 or Llama 3.1 70B Instruct open source?
DeepSeek R1 is listed under Open Source. Llama 3.1 70B 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 reasoning mode, DeepSeek R1 or Llama 3.1 70B Instruct?
DeepSeek R1 has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for structured outputs, DeepSeek R1 or Llama 3.1 70B Instruct?
Both DeepSeek R1 and Llama 3.1 70B Instruct expose structured outputs. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run DeepSeek R1 and Llama 3.1 70B Instruct?
DeepSeek R1 is available on DeepSeek Platform, OpenRouter, Together AI, Fireworks AI, and NVIDIA NIM. Llama 3.1 70B Instruct is available on OctoAI API, Together AI, Fireworks AI, NVIDIA NIM, and Microsoft Foundry. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.