Model crosswalk
Side-by-side on price, capability and workload — three-way comparison.
Codestral 22B
vs
Qwen 2.5 Coder 32B Instruct
vs
Refact Llama 3.1 70B
Codestral 22BA
Codestral 22B
22B params · 33K context · mistral-research
Cheapest provider—
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$/1M output—
Qwen 2.5 Coder 32B InstructB
Qwen 2.5 Coder 32B Instruct
32B params · 131K context · qwen
Cheapest provider—
$/1M input—
$/1M output—
Refact Llama 3.1 70BC
Refact Llama 3.1 70B
70B params · 131K context · llama-3
Cheapest provider—
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$/1M output—
Specs and cheapest providers
| Spec | Codestral 22B | Qwen 2.5 Coder 32B Instruct | Refact Llama 3.1 70B |
|---|---|---|---|
| Parameters | 22B | 32B | 70B |
| Context window | 33K tokens | 131K tokens | 131K tokens |
| License | mistral-research | qwen | llama-3 |
| Released | 2024-05-29 | 2024-11-12 | 2024-09-01 |
| Cheapest provider | |||
| Provider | — | — | — |
| Input / 1M tokens | — | — | — |
| Output / 1M tokens | — | — | — |
Benchmark comparison
No benchmark data available yet.
Editor's take
Three coding-oriented models at different sizes, each with a distinct target use case and a different story on commercial viability.
Codestral 22B is Mistral AI's first coding specialist — 22 billion parameters, 80-plus language support, and a 32K context window released in May 2024. HumanEval scores compete with same-generation peers like DeepSeek Coder V2 Lite. The practical ceiling here is the Mistral Research License: commercial production use requires a direct licensing agreement with Mistral AI. For teams building user-facing products, this is a hard gate rather than a fine-print detail.
Qwen 2.5 Coder 32B Instruct, from Alibaba's November 2024 release, extends code specialization to 32 billion parameters with a 131K context window and support for 92 programming languages. On LiveCodeBench and MultiPL-E it benchmarks alongside DeepSeek Coder V2 in the credible production tier. The Qwen license permits commercial deployment. Hosted across DeepInfra and other inference providers, per-token costs remain below frontier-tier models while delivering stronger multi-file reasoning than sub-15B options.
Refact Llama 3.1 70B, co-released by Together Computer and Refact AI in September 2024, is a fine-tune of Meta's Llama 3.1 70B base targeting IDE tab-completion and agentic refactoring workflows. The 128K context window is its headline specification — it comfortably ingests large file trees or multi-file diffs in a single pass, which is exactly the bottleneck in embedded IDE pipelines. This is a niche model: it makes sense if your product is an IDE extension or an agentic refactoring loop, not a general chat backend. It inherits the Llama 3 community license, which permits commercial use.
Pick Codestral 22B for non-commercial research. Pick Qwen 2.5 Coder 32B for production API code generation and CI pipelines. Pick Refact Llama 3.1 70B specifically for IDE-as-a-product contexts where the 128K context window and refactoring-focused fine-tuning justify the 70B inference cost.
Compare two at a time
Frequently asked questions
- How does Codestral 22B compare to Qwen 2.5 Coder 32B Instruct and Refact Llama 3.1 70B on price?
- Use the table above to compare input and output prices per 1M tokens across the cheapest available providers for each model.
- Which model is best for coding: Codestral 22B, Qwen 2.5 Coder 32B Instruct, or Refact Llama 3.1 70B?
- HumanEval and other code benchmarks are shown in the table. For production code tasks, also consider context window size and provider latency.
- What is the context window for Codestral 22B, Qwen 2.5 Coder 32B Instruct, and Refact Llama 3.1 70B?
- Context window sizes are listed in the Specs row of the comparison table above.
Full model details