DeepSeek-R1 7B: pricing, context window and benchmarks
DeepSeek-R1 7B is a small open-weight model from DeepSeek. It offers a 32,768-token context window, costs $1.79 per million input tokens and $9.81 per million output tokens, and averages 63.0 across the index's benchmark suite.
Pricing
DeepSeek-R1 7B costs $1.79 per million input tokens and $9.81 per million output tokens. A blended 3:1 input-to-output mix works out to about $3.79 per million tokens. Cached input is listed at $0.26 per million tokens.
| Item | Price | Notes |
|---|---|---|
| Input | $1.79 | per 1M tokens |
| Output | $9.81 | per 1M tokens |
| Cached input | $0.26 | per 1M tokens |
| Blended 3:1 | $3.79 | estimate per 1M tokens |
| 1M in + 1M out | $11.60 | estimate |
Benchmarks
Scores below are modelled estimates on a 0–100 scale. Use them to compare relative position, not as official vendor results.
| Benchmark | Score | Rank | Percentile | Relative |
|---|---|---|---|---|
| MMLU-Pro | 69.4 | 402 | 33th | |
| GPQA Diamond | 57.7 | 431 | 28th | |
| SWE-bench Verified | 53.1 | 397 | 34th | |
| HumanEval | 65.3 | 437 | 27th | |
| MATH-500 | 64.0 | 424 | 29th | |
| AIME 2025 | 53.0 | 434 | 28th | |
| LiveCodeBench | 52.2 | 425 | 29th | |
| IFEval | 71.7 | 434 | 28th | |
| TruthfulQA | 67.5 | 423 | 30th | |
| HellaSwag | 77.3 | 411 | 32th | |
| MMMU | 61.8 | 410 | 32th | |
| Arena Elo | 1297.5 | 424 | 29th |
What DeepSeek-R1 7B is good for
DeepSeek-R1 7B is a small model. That makes it a good fit for classification, extraction, routing, summarization and other high-volume jobs where latency and cost dominate. It is not the right pick for open-ended frontier reasoning, but at $1.79 per million input tokens it can handle a large share of production traffic.
Strengths
- Input price of $1.79 per million tokens is at or below the index median.
- Open weights make self-hosting, fine-tuning and data-residency review possible.
- Accepts more than text, including image input where the provider supports it.
Trade-offs
- Average benchmark score is below the index median; test it on your own task.
- Less reliable on open-ended reasoning and complex multi-step instructions.
How it compares
| Model | Provider | Context | Input / 1M | Avg score |
|---|---|---|---|---|
| DeepSeek-V3.2 7B | DeepSeek | 4096 | $1.75 | 63.2 |
| Firefunction Mini | Fireworks AI | 32768 | $4.63 | 63.2 |
| GLM-4.6 8B | Zhipu AI | 8192 | $1.69 | 63.1 |
| SmolLM3 | Hugging Face | 8192 | $1.71 | 63.1 |
| DeepSeek-R1 7B | DeepSeek | 32768 | $1.79 | 63.0 |
| Zephyr | Hugging Face | 8192 | $1.61 | 62.8 |
FAQ
How much does DeepSeek-R1 7B cost?
DeepSeek-R1 7B is listed at $1.79 per million input tokens and $9.81 per million output tokens. Cached input is $0.26 per million tokens. A blended 3:1 input-to-output mix is about $3.79 per million tokens.
What is the context window of DeepSeek-R1 7B?
DeepSeek-R1 7B has a context window of 32,768 tokens and can emit up to 4,096 output tokens per request in this index.
Is DeepSeek-R1 7B open weights?
Yes. DeepSeek-R1 7B is listed as an open-weight model under a open weights licence.
How does DeepSeek-R1 7B score on benchmarks?
DeepSeek-R1 7B averages 63.0 across the scored benchmarks in this index, ranking #420 of 600 models. Its strongest relative result is Arena Elo at 1297.5.
What is DeepSeek-R1 7B best for?
DeepSeek-R1 7B is a small model. That makes it a good fit for classification, extraction, routing, summarization and other high-volume jobs where latency and cost dominate. It is not the right pick for open-ended frontier reasoning, but at $1.79 per million input tokens it can handle a large share of production traffic.