o1-class reasoning performance at under $0.60/1M input tokens
Open-source weights — can be self-hosted for sensitive workloads
Explicit chain-of-thought reasoning makes outputs auditable
Weaknesses
Slow — deliberate reasoning takes significantly longer than standard models
Overkill for routine tasks where a faster model gets the same result
Same data sovereignty concerns as DeepSeek V3 for regulated industries
Real-world use cases
What people actually use DeepSeek R1 for.
Complex algorithm design and mathematical problem-solving where chain-of-thought reasoning matters
Scientific research synthesis requiring structured multi-step analysis
Hard coding challenges and competitive programming at low cost compared to o1
How DeepSeek R1 compares
The nearest models people weigh against it, and what actually separates them.
vs DeepSeek V3 — Against DeepSeek V3 (DeepSeek), DeepSeek R1 costs about 50% more per token and answers slower. DeepSeek V3 is the one to check first if the price difference matters more than the ceiling.
vs Claude 3.5 Sonnet — Against Claude 3.5 Sonnet (Anthropic), DeepSeek R1 runs about 92% cheaper per token, gives up 1.6x on context and answers slower. Which one wins depends on whether context depth or latency is your constraint.
vs Claude 3.7 Sonnet (thinking) — Against Claude 3.7 Sonnet (thinking) (Anthropic), DeepSeek R1 runs about 85% cheaper per token, gives up 1.6x on context and answers slower. Which one wins depends on whether context depth or latency is your constraint.
Price History
DeepSeek R1 pricing over time
→0% since May 31
90 data points · tracked daily since May 31, 2026
Ready to try it?
Start using DeepSeek R1
Math, science, complex reasoning, and multi-step problem solving at budget cost. Start free — no card required.
Open-source frontier model from DeepSeek that matches GPT-4o class performance at a fraction of the cost — the most disruptive budget option for coding and general tasks.
Verdict
GPT-4o-class coding quality at under $0.30/1M — the best value in the directory.
Quality score
71%
Pricing
$0.27/1M in
$1.10/1M out
Speed
Fast
4/5 speed
Context
128k tokens
DeepSeek V3 shocked the market on release. At this price point with this capability level, it forces a reconsideration of when premium models are actually worth it.
Open sourceBudgetCodingDeepSeek
Best for
Coding, reasoning, and general tasks at extreme cost efficiency
Claude 3.5 Sonnet is Anthropic's mid-cycle flagship model, balancing strong reasoning, coding, and instruction-following with a 200K context window. It sits between Haiku and Opus in Anthropic's lineup, offering near-flagship quality at a lower cost than top-tier models.
Verdict
One of the best models for coding and complex instruction-following, but its premium pricing demands premium use cases.
Quality score
81%
Pricing
$6.00/1M in
$30.00/1M out
Speed
Balanced
3/5 speed
Context
200k tokens
Pricing at $6 input / $30 output per million tokens is significantly higher than GPT-4o ($2.50/$10). Best accessed via Anthropic API or Amazon Bedrock. Claude 3.5 Sonnet (October 2024 version) supersedes the June 2024 release with improved performance.
Claude 3.7 Sonnet with extended thinking enabled — Anthropic's hybrid reasoning model that explicitly deliberates before responding, surfacing its chain-of-thought for complex multi-step problems. It sits between standard Sonnet and full reasoning-only models, balancing depth with practical usability.
Verdict
The most transparent reasoning model on the market — ideal when you need to see and trust the thought process, not just the answer.
Quality score
73%
Pricing
$3.00/1M in
$15.00/1M out
Speed
Deliberate
2/5 speed
Context
200k tokens
Thinking tokens (the internal reasoning trace) count toward output token billing, which can significantly increase costs on complex queries. The thinking budget can often be configured via the API. Best used selectively for tasks that genuinely benefit from deliberation rather than as a default model.
ReasoningExtended ThinkingCodingAgenticAnthropic
Best for
Tackling complex coding challenges, mathematical proofs, and multi-step logical problems where visible reasoning and higher accuracy matter more than speed.
DeepSeek R1 costs $0.55 per million input tokens and $2.19 per million output tokens on the API. A month of 10M input and 2M output tokens runs about $9.88 at list price, before any batch or caching discounts.
What is the context window of DeepSeek R1?
DeepSeek R1 has a 128k tokens context window, with up to 8k tokens of output per response. That is the total of prompt plus response the model can hold in one request.
What is the knowledge cutoff of DeepSeek R1?
DeepSeek R1's training data runs through July 2024, and the model was released on January 20, 2025. For anything after that date it needs web search or documents in the prompt.
What is DeepSeek R1 best for?
DeepSeek R1 is best for math, science, complex reasoning, and multi-step problem solving at budget cost. It is a strong fit when that workflow matters more than the tradeoffs around budget pricing and deliberate speed.
When should I avoid DeepSeek R1?
Speed matters — R1's deliberate reasoning makes it wrong for interactive or high-throughput use cases.
What is a cheaper alternative to DeepSeek R1?
DeepSeek V3 (DeepSeek) at $0.27/1M/1M input against DeepSeek R1's $0.55/1M/1M — roughly 50% less per token all in. GPT-4o-class coding quality at under $0.30/1M — the best value in the directory. Compare it first if DeepSeek R1's pricing is the thing stopping you.
What is a faster alternative to DeepSeek R1?
Claude 3.5 Sonnet — balanced against DeepSeek R1's deliberate, with 200k tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.
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