| Signal | GPT-3.5 Turbo | Delta | Codestral 2508 |
|---|---|---|---|
Capabilities | 50 | -- | |
Pricing | 99 | -1 | |
Context window size | 67 | -19 | |
Recency | 0 | -81 | |
Output Capacity | 60 | +40 | |
| Overall Result | 1 wins | of 5 | 3 wins |
Score History
40
current score
Tied
right now
40
current score
OpenAI
Mistral AI
Codestral 2508 saves you $50.00/month
That's $600.00/year compared to GPT-3.5 Turbo at your current usage level of 100K calls/month.
| Metric | GPT-3.5 Turbo | Codestral 2508 | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #309 | #262 | Codestral 2508 |
| Quality Rank | #309 | #262 | Codestral 2508 |
| Adoption Rank | #309 | #262 | Codestral 2508 |
| Parameters | -- | -- | -- |
| Context Window | 16K | 256K | Codestral 2508 |
| Pricing | $0.50/$1.50/M | $0.30/$0.90/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | GPT-3.5 Turbo |
| Pricing | 99 | 99 | Codestral 2508 |
| Context window size | 67 | 86 | Codestral 2508 |
| Recency | 0 | 82 | Codestral 2508 |
| Output Capacity | 60 | 20 | GPT-3.5 Turbo |
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 #309), placing it in the top -6% of all 290 models tracked.
Scores 40/100 (rank #262), placing it in the top 10% 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.
Codestral 2508 offers 40% better value per quality point. At 1M tokens/day, you'd spend $18.00/month with Codestral 2508 vs $30.00/month with GPT-3.5 Turbo - a $12.00 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
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. 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 (40/100) correlates with better nuance, coherence, and style in long-form content
GPT-3.5 Turbo and Codestral 2508 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
GPT-3.5 Turbo
Marginally better benchmark scores; both are excellent
Best for Cost
Codestral 2508
40% lower pricing; better value at scale
Best for Reliability
GPT-3.5 Turbo
Higher uptime and faster response speeds
Best for Prototyping
GPT-3.5 Turbo
Stronger community support and better developer experience
Best for Production
GPT-3.5 Turbo
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-3.5 Turbo | Codestral 2508 |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
OpenAI
Mistral AI
Codestral 2508 saves you $1.08/month
That's 40% cheaper than GPT-3.5 Turbo 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 | GPT-3.5 Turbo | Codestral 2508 |
|---|---|---|
| Context Window | 16K | 256K |
| Max Output Tokens | 4,096 | -- |
| Open Source | No | No |
| Created | May 28, 2023 | Aug 1, 2025 |