DeepSeek Reasoner (R1) vs Llama 3.3 70B
Performance benchmarks + pricing comparison — updated April 2026
DeepSeek Reasoner (R1)
DeepSeekDeepSeek's reasoning model. Comparable to OpenAI's o1 but at much lower cost.
| Input | $0.550/M |
| Output | $2.19/M |
| Context | 128K tokens |
| Best For | Complex reasoning, math, advanced coding |
| Benchmark | 72/100 |
Llama 3.3 70B
MetaMeta's open-weight 70B model. Strong coding and general capability, widely supported across AI platforms.
| Input | $0.250/M |
| Output | $1.00/M |
| Context | 128K tokens |
| Best For | Self-hosted deployments, cost-effective coding, custom fine-tuning |
Cost Comparison by Scenario
Estimated cost per project with 30% cache hit rate. Actual costs may vary based on usage patterns.
| Scenario | DeepSeek Reasoner (R1) | Llama 3.3 70B | Savings |
|---|---|---|---|
| Small Script (1K lines) | $0.08 | $0.04 | Llama 3.3 70B saves $0.05 (54%) |
| Medium Feature (10K lines) | $0.63 | $0.29 | Llama 3.3 70B saves $0.34 (54%) |
| Large Project (50K lines) | $3.15 | $1.44 | Llama 3.3 70B saves $1.71 (54%) |
| Code Review (5K lines) | $0.15 | $0.07 | Llama 3.3 70B saves $0.08 (54%) |
Verdict
Llama 3.3 70B wins on both price and performance — $0.250/M input with a benchmark score of N/A/100.
For most developers, this is the clear choice between these two models.
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