DeepSeek-R1 for reasoning
DeepSeek-R1 is ranked #4 on LLMDex's llm for reasoning ranking out of 6 models we track for this use case. Below, the specific reasons it slots where it does, and when you should reach for an alternative.
Updated
At a glance
- Rank
- #4 of 6
- Context
- 128K tokens
- Output / 1M
- $2.19 / 1M tokens
- Released
- Jan 2025
Why DeepSeek-R1 fits this task
Three things about DeepSeek-R1 that map directly onto what this task rewards: Open-weight reasoning model on par with o1; Cheap reasoning per token. Beyond the task-specific fit, DeepSeek-R1 also brings mit license, both of which compound when the workload broadens.
The criteria this task rewards
LLMDex ranks best llm for reasoning on 5 criteria , these are the axes the ranking uses, in priority order:
- GPQA Diamond performance
- ARC-AGI public set scores
- Chain-of-thought coherence on novel puzzles
- Reasoning-token cost, expensive on flagship reasoning models
- Latency budget, reasoning runs are slow by design
How DeepSeek-R1 scores on each axis
Where DeepSeek-R1 costs you: slow, reasoning is slow by design. For most teams this is acceptable on this workload, the value of the strengths above outweighs the cost. For cost-bound workloads or teams with strict latency budgets, run an eval against the next two ranked models on real data before committing.
Strengths that pay off here
- Open-weight reasoning model on par with o1
- MIT license
- Cheap reasoning per token
Tracked weaknesses
- Slow, reasoning is slow by design
- No vision
When to pick something else
If you can pay slightly more or accept slightly different tradeoffs, Claude Opus 4.7 from Anthropic ranks one position higher and tends to win on the hardest cases. Anthropic's mid-2026 flagship, ahead on SWE-bench, agent reliability, and writing quality.
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Other models for reasoning
- o3 for reasoning
OpenAI's flagship reasoning model, set the bar for hard math, GPQA, and agent benchmarks in 2025.
Read guide - GPT-5.5 for reasoning
OpenAI's mid-cycle GPT-5 refresh, improved reasoning, tool use, and multimodal grounding over the 2025 launch.
Read guide - Claude Opus 4.7 for reasoning
Anthropic's mid-2026 flagship, ahead on SWE-bench, agent reliability, and writing quality.
Read guide - Gemini 3 Pro for reasoning
Google's late-2025 flagship, set new benchmarks on long-context, vision, and reasoning at competitive pricing.
Read guide - o4 for reasoning
OpenAI's late-2025 standalone reasoning model, an evolution of o3 with deeper chain-of-thought and stronger multimodal reasoning.
Read guide
DeepSeek-R1 for other use cases
Direct comparisons
Frequently asked
Is DeepSeek-R1 good for reasoning?
DeepSeek-R1 is ranked #4 on LLMDex's reasoning list. First open-weight reasoning model to match o1, the release that proved RL-from-scratch reasoning training was reproducible.How much does DeepSeek-R1 cost for reasoning?
DeepSeek-R1 costs $0.55 / 1M tokens for input tokens and $2.19 / 1M tokens for output tokens. For reasoning workloads, output costs typically dominate; budget on the higher number.What's a cheaper alternative to DeepSeek-R1 for reasoning?
The next ranked model on this task is Gemini 3 Pro. Compare both before committing.When should I NOT use DeepSeek-R1 for reasoning?
Tracked weakness: Slow, reasoning is slow by design. If that constraint is binding for your workload, the next-ranked model on this task is the safer pick.
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