DeepSeek R1 vs Phi 3.5 Mini Instruct
DeepSeek R1 (2025) and Phi 3.5 Mini Instruct (2024) are frontier reasoning models from DeepSeek and Microsoft Research. DeepSeek R1 ships a 128K-token context window, while Phi 3.5 Mini Instruct ships a 128K-token context window. On pricing, DeepSeek R1 costs $0.1/1M input tokens versus $0.9/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
DeepSeek R1 is ~800% cheaper at $0.1/1M; pay for Phi 3.5 Mini Instruct only for provider fit.
Specs
| Released | 2025-01-20 | 2024-08-20 |
| Context window | 128K | 128K |
| Parameters | 671B, 37B Active | 3.8B |
| Architecture | decoder only | decoder only |
| License | Open Source | MIT |
| Knowledge cutoff | - | - |
Pricing and availability
| DeepSeek R1 | Phi 3.5 Mini Instruct | |
|---|---|---|
| Input price | $0.1/1M tokens | $0.9/1M tokens |
| Output price | $0.3/1M tokens | $0.9/1M tokens |
| Providers |
Capabilities
| DeepSeek R1 | Phi 3.5 Mini Instruct | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: DeepSeek R1, structured outputs: DeepSeek R1, and code execution: DeepSeek R1. Both models share the core language-model surface, 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 Phi 3.5 Mini Instruct lists $0.9/1M input and $0.9/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek R1 lower by about $0.74 per million blended tokens. Availability is 13 providers versus 2, 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 Phi 3.5 Mini 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. 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 R1 or Phi 3.5 Mini Instruct?
DeepSeek R1 supports 128K tokens, while Phi 3.5 Mini 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 Phi 3.5 Mini Instruct?
DeepSeek R1 is cheaper on tracked token pricing. DeepSeek R1 costs $0.1/1M input and $0.3/1M output tokens. Phi 3.5 Mini Instruct costs $0.9/1M input and $0.9/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek R1 or Phi 3.5 Mini Instruct open source?
DeepSeek R1 is listed under Open Source. Phi 3.5 Mini Instruct is listed under MIT. 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 Phi 3.5 Mini 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 Phi 3.5 Mini Instruct?
DeepSeek R1 has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run DeepSeek R1 and Phi 3.5 Mini Instruct?
DeepSeek R1 is available on DeepSeek Platform, OpenRouter, Together AI, Fireworks AI, and NVIDIA NIM. Phi 3.5 Mini Instruct is available on Fireworks AI and NVIDIA NIM. 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.