Simulating realistic AI coding assistant parameters (12,000 in / 2,000 out with 60% cache reuse). Qwen 2.5 Coder 32B delivers a 33% cost reduction over Codestral 2501.
Quick answer
For AI coding assistant, Qwen 2.5 Coder 32B is the lower-cost option at $0.002304 per request versus $0.003456 for Codestral 2501, a modeled saving of 33%.
Method & trust
The comparison uses 12,000 input tokens, 2,000 output tokens, and 60% cache reuse for the selected workload. Pricing is applied per model, then scaled to monthly request volumes.
| Traffic Volume Tier | Qwen 2.5 Coder 32B Monthly | Codestral 2501 Monthly | Monthly Savings by picking Qwen 2.5 Coder 32B |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $2.304 | $3.456 | Save $1.152 / mo |
| 10,000 reqs/mo (Small App) | $23.04 | $34.56 | Save $11.52 / mo |
| 100,000 reqs/mo (Growth Production) | $230.40 | $345.60 | Save $115.20 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $2,304.00 | $3,456.00 | Save $1,152.00 / mo |
Qwen 2.5 Coder 32B is 33% cheaper for AI coding assistant workloads. At standard AI coding assistant parameter ratios (12,000 input tokens, 2,000 output tokens, 60% cache hit), Qwen 2.5 Coder 32B costs $0.002304 per request compared to $0.003456 on Codestral 2501.
Qwen 2.5 Coder 32B offers a context window of 128,000 tokens (max output: 8,192), while Codestral 2501 offers 256,000 tokens (max output: 8,192).
At 100,000 requests per month, using Qwen 2.5 Coder 32B saves $115.20 every month (or $1,382.40 annually) compared to Codestral 2501.
Output is the expensive side — prefer models with cheap output for autocomplete-style calls. Cache repository context between keystrokes; diffs change far less than the full file. Measure acceptance rate: paying for output users delete is pure waste.