DeepSeek: R1
Analysis Summary
DeepSeek R1 is a text-only reasoning model with a 163K context window, tool use, and function calling. Its measured intelligence and coding results are stronger than the other low-cost reasoning models in this batch, while the long context supports substantial technical and analytical prompts. Pricing remains low enough for production experimentation and selected high-volume tasks.
It fits code review, technical problem solving, structured research, and document analysis where deliberate reasoning is valuable. The measured agentic result is weak, so external tools should be used within bounded workflows with explicit validation rather than open-ended autonomy. It is also text-only, which limits image-based agency and content review. Adopt R1 for economical technical reasoning and pair it with a stronger or more reliable model for high-stakes client communication and autonomous execution.
Assessed August 9, 2026
Editorial notes
DeepSeek R1 combines a 163K context window, low pricing, tool use, and stronger coding and reasoning results than most budget models, though weak agentic performance limits autonomous deployment.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
DeepSeek R1 combines a 163K context window, low pricing, tool use, and stronger coding and reasoning results than most budget models, though weak agentic performance limits autonomous deployment.
How DeepSeek: R1 compares
DeepSeek: R1 ranks #177 of 432 AI models we track for overall intelligence, #129 of 205 for coding, #142 of 187 for agentic tasks. Its 64K-token context window is larger than 26% of the models we list. At $0.70 per million input tokens it is cheaper than 32% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on content. The pulled-in technical corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.70 | $0.000700 |
| Output | $2.50 | $0.002500 |
What would DeepSeek: R1 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 743 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save DeepSeek: R1 for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout DeepSeek: R1
DeepSeek R1 is here: Performance on par with OpenAI o1, but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass..
Frequently asked questions about DeepSeek: R1
How much does DeepSeek: R1 cost?
DeepSeek: R1 costs $0.70 per million input tokens and $2.50 per million output tokens.
What is the context window of DeepSeek: R1?
DeepSeek: R1 has a context window of 64,000 tokens (64K).
Is DeepSeek: R1 good for coding?
On our coding benchmark index, DeepSeek: R1 ranks #129 of 205 models, placing it in the broader range of the field for code generation and debugging.
What can DeepSeek: R1 do?
DeepSeek: R1 supports tool use and function calling.
Who created DeepSeek: R1?
DeepSeek: R1 is developed by DeepSeek and was released on January 20, 2025.