| Signal | Codestral 2508 | Delta | Qwen3 30B A3B Instruct 2507 |
|---|---|---|---|
Capabilities | 50 | -- | |
Pricing | 99 | -1 | |
Context window size | 77 | +4 | |
Recency | 73 | +1 | |
Output Capacity | 20 | -55 | |
| Overall Result | 2 wins | of 5 | 2 wins |
Score History
40
current score
Tied
right now
40
current score
Mistral AI
Alibaba
Qwen3 30B A3B Instruct 2507 saves you $60.53/month
That's $726.39/year compared to Codestral 2508 at your current usage level of 100K calls/month.
| Metric | Codestral 2508 | Qwen3 30B A3B Instruct 2507 | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #249 | #251 | Codestral 2508 |
| Quality Rank | #249 | #251 | Codestral 2508 |
| Adoption Rank | #249 | #251 | Codestral 2508 |
| Parameters | -- | 30B | -- |
| Context Window | 256K | 131K | Codestral 2508 |
| Pricing | $0.30/$0.90/M | $0.05/$0.19/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | Codestral 2508 |
| Pricing | 99 | 100 | Qwen3 30B A3B Instruct 2507 |
| Context window size | 77 | 73 | Codestral 2508 |
| Recency | 73 | 73 | Codestral 2508 |
| Output Capacity | 20 | 75 | Qwen3 30B A3B Instruct 2507 |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 40/100 (rank #249), placing it in the top 14% of all 290 models tracked.
Scores 40/100 (rank #251), placing it in the top 14% of all 290 models tracked.
With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Qwen3 30B A3B Instruct 2507 offers 80% better value per quality point. At 1M tokens/day, you'd spend $3.62/month with Qwen3 30B A3B Instruct 2507 vs $18.00/month with Codestral 2508 - a $14.38 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Qwen3 30B A3B Instruct 2507 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (256K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.19/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (40/100) correlates with better nuance, coherence, and style in long-form content
Codestral 2508 and Qwen3 30B A3B Instruct 2507 are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Codestral 2508
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3 30B A3B Instruct 2507
80% lower pricing; better value at scale
Best for Reliability
Codestral 2508
Higher uptime and faster response speeds
Best for Prototyping
Codestral 2508
Stronger community support and better developer experience
Best for Production
Codestral 2508
Wider enterprise adoption and proven at scale
by Mistral AI
| Capability | Codestral 2508 | Qwen3 30B A3B Instruct 2507 |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Mistral AI
Alibaba
Qwen3 30B A3B Instruct 2507 saves you $1.30/month
That's 80% cheaper than Codestral 2508 at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Codestral 2508 | Qwen3 30B A3B Instruct 2507 |
|---|---|---|
| Context Window | 256K | 131K |
| Max Output Tokens | -- | 32,000 |
| Open Source | No | Yes |
| Created | Aug 1, 2025 | Jul 29, 2025 |