DeepSeek Coder 33B vs Code Llama 34B: Benchmark Comparison
Detailed comparison of DeepSeek Coder 33B and Code Llama 34B covering benchmarks, pricing, context window, and compliance.
Key Specifications
| Specification | DeepSeek Coder 33B | Code Llama 34B |
|---|---|---|
| Vendor | deepseek | meta |
| Version | coder-33b | code-llama-34b |
| Release Date | 2024-01-25 | 2023-08-24 |
| Context Window | 16384 tokens | 16000 tokens |
| Input Modalities | text | text |
| Output Modalities | text | text |
| License | DeepSeek License | Llama 2 Community License |
| SOC2 | ✗ | ✗ |
| HIPAA | ✗ | ✗ |
| GDPR | ✗ | ✗ |
| ISO 27001 | ✗ | ✗ |
Benchmark Results
| Benchmark | DeepSeek Coder 33B | Code Llama 34B | Winner |
|---|---|---|---|
| ARC | 92.2 | 88.7 | DeepSeek Coder 33B |
| BBH | 61.6 | 59.1 | DeepSeek Coder 33B |
| GPQA | 26.8 | 27 | Code Llama 34B |
| GSM8K | 69.7 | 59.8 | DeepSeek Coder 33B |
| HUMANEVAL | 71.8 | 71.7 | DeepSeek Coder 33B |
| IFEVAL | 58.8 | 58.7 | DeepSeek Coder 33B |
| MATH | 32.1 | 44.7 | Code Llama 34B |
| MMLU | 65.9 | 74.5 | Code Llama 34B |
| MUSR | 45.8 | 44.9 | DeepSeek Coder 33B |
| WINOGRANDE | 79.8 | 80 | Code Llama 34B |
Pricing Comparison
| Tier (per Mtok) | DeepSeek Coder 33B | Code Llama 34B |
|---|---|---|
| Input | $0.28 | $0.5 |
| Output | $0.28 | $0.5 |
| Cache Read | $0 | $0 |
| Cache Write | $0 | $0 |
DeepSeek Coder 33B vs Code Llama 34B
Model Overview
DeepSeek Coder 33B and Code Llama 34B are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.
Key Specifications
| Vendor | Release Date | Context Window | License |
|---|---|---|---|
| Deepseek / Meta | 2024-01-25 / 2023-08-24 | 16K / 16K | DeepSeek License / Llama 2 Community License |
Benchmark Performance
| Benchmark | DeepSeek Coder 33B | Code Llama 34B | Winner |
|---|---|---|---|
| ARC | 92.2 | 88.7 | A |
| BBH (BIG-Bench Hard) | 61.6 | 59.1 | A |
| GPQA | 26.8 | 27.0 | Tie |
| GSM8K (Grade School Math 8K) | 69.7 | 59.8 | A |
| HumanEval | 71.8 | 71.7 | Tie |
| IFEval | 58.8 | 58.7 | Tie |
| MATH | 32.1 | 44.7 | B |
| MMLU (Massive Multitask Language Understanding) | 65.9 | 74.5 | B |
| MUSR | 45.8 | 44.9 | A |
| WinoGrande | 79.8 | 80.0 | Tie |
Pricing Comparison
| Input | Output | Cache Read | Cache Write |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
per million tokens — A / B
Strengths & Weaknesses
DeepSeek Coder 33B
- ✅ Reliable general-purpose model.
- ⚠️ Proprietary, not self-hostable.
- ⚠️ Context window 16K is limited.
Code Llama 34B
- ✅ Reliable general-purpose model.
- ⚠️ Proprietary, not self-hostable.
- ⚠️ Context window 16K is limited.
Editor’s Take
DeepSeek Coder 33B and Code Llama 34B each have their strengths. Choose based on workload (code, long context, vision), referencing the tables above.
FAQ
Which model is better for coding tasks?
Refer to the HumanEval benchmark table; the model with a higher score is better suited for coding tasks.
Which model is cheaper?
Refer to the pricing comparison table above; the model with lower input/output prices is more cost-effective.
Which has a longer context window?
Refer to the key specifications table; the model with a larger context window is better for long documents.
References
Editor's Take
See Editor's Take section.