| Signal | Codestral 2508 | Delta | o3 Deep Research |
|---|---|---|---|
Capabilities | 50 | -50 | |
Pricing | 1 | -39 | |
Context window size | 86 | +2 | |
Recency | 92 | -8 | |
Output Capacity | 20 | -63 | |
| Overall Result | 1 wins | of 5 | 4 wins |
0
days ranked higher
0
days
30
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Mistral AI
OpenAI
Codestral 2508 saves you $2925.00/month
That's $35100.00/year compared to o3 Deep Research at your current usage level of 100K calls/month.
| Metric | Codestral 2508 | o3 Deep Research | Winner |
|---|---|---|---|
| Overall Score | 61 | 94 | o3 Deep Research |
| Rank | #193 | #15 | o3 Deep Research |
| Quality Rank | #193 | #15 | o3 Deep Research |
| Adoption Rank | #193 | #15 | o3 Deep Research |
| Parameters | -- | -- | -- |
| Context Window | 256K | 200K | Codestral 2508 |
| Pricing | $0.30/$0.90/M | $10.00/$40.00/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 100 | o3 Deep Research |
| Pricing | 1 | 40 | o3 Deep Research |
| Context window size | 86 | 84 | Codestral 2508 |
| Recency | 92 | 100 | o3 Deep Research |
| Output Capacity | 20 | 83 | o3 Deep Research |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 61/100 (rank #193), placing it in the top 34% of all 290 models tracked.
Scores 94/100 (rank #15), placing it in the top 95% of all 290 models tracked.
o3 Deep Research has a 33-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Codestral 2508 offers 98% better value per quality point. At 1M tokens/day, you'd spend $18.00/month with Codestral 2508 vs $750.00/month with o3 Deep Research — a $732.00 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
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Codestral 2508 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 ($0.90/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (94/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input — can analyze screenshots, diagrams, photos, and scanned documents directly
o3 Deep Research clearly outperforms Codestral 2508 with a significant 33.3-point lead. For most general use cases, o3 Deep Research is the stronger choice. However, Codestral 2508 may still excel in niche scenarios.
Best for Quality
Codestral 2508
Marginally better benchmark scores; both are excellent
Best for Cost
Codestral 2508
98% 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 | o3 Deep Research |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
Mistral AI
OpenAI
Codestral 2508 saves you $64.38/month
That's 98% cheaper than o3 Deep Research 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 | o3 Deep Research |
|---|---|---|
| Context Window | 256K | 200K |
| Max Output Tokens | -- | 100,000 |
| Open Source | No | No |
| Created | Aug 1, 2025 | Oct 10, 2025 |
o3 Deep Research scores 94/100 (rank #15) compared to Codestral 2508's 61/100 (rank #193), giving it a 33-point advantage. o3 Deep Research is the stronger overall choice, though Codestral 2508 may excel in specific areas like cost efficiency.
Codestral 2508 is ranked #193 and o3 Deep Research is ranked #15 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Codestral 2508 is cheaper at $0.90/M output tokens vs o3 Deep Research's $40.00/M output tokens — 44.4x more expensive. Input token pricing: Codestral 2508 at $0.30/M vs o3 Deep Research at $10.00/M.
Codestral 2508 has a larger context window of 256,000 tokens compared to o3 Deep Research's 200,000 tokens. A larger context window means the model can process longer documents and conversations.