GPT-3.5 Turbo (batch) vs Mistral Small 3.1 24B
| Signal | GPT-3.5 Turbo (batch) | Delta | Mistral Small 3.1 24B |
|---|---|---|---|
Capabilities | 67 | +33 | |
Pricing | 99 | 0 | |
Context window size | 67 | -14 | |
Recency | 0 | -40 | |
Output Capacity | 60 | -25 | |
| Overall Result | 1 wins | of 5 | 4 wins |
Score History
40
current score
Tied
right now
40
current score
GPT-3.5 Turbo (batch)
OpenAI
Mistral Small 3.1 24B
Mistral AI
GPT-3.5 Turbo (batch) saves you $0.35/month
That's $4.20/year compared to Mistral Small 3.1 24B at your current usage level of 100K calls/month.
| Metric | GPT-3.5 Turbo (batch) | Mistral Small 3.1 24B | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #363 | #338 | Mistral Small 3.1 24B |
| Quality Rank | #363 | #338 | Mistral Small 3.1 24B |
| Adoption Rank | #363 | #338 | Mistral Small 3.1 24B |
| Parameters | -- | 24B | -- |
| Context Window | 16K | 128K | Mistral Small 3.1 24B |
| Pricing | $0.25/$0.75/M | $0.35/$0.55/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 33 | GPT-3.5 Turbo (batch) |
| Pricing | 99 | 99 | Mistral Small 3.1 24B |
| Context window size | 67 | 81 | Mistral Small 3.1 24B |
| Recency | 0 | 40 | Mistral Small 3.1 24B |
| Output Capacity | 60 | 85 | Mistral Small 3.1 24B |
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 #363), placing it in the top -25% of all 290 models tracked.
Scores 40/100 (rank #338), placing it in the top -16% 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.
Choose GPT-3.5 Turbo (batch) when you need:
- Agentic applications using tool/function calling
Choose Mistral Small 3.1 24B when you need:
- Processing long documents or large codebases (128K token context)
- Multimodal workflows that require image understanding
- Self-hosted deployments where you need full control over the model
Mistral Small 3.1 24B offers 9% better value per quality point. At 1M tokens/day, you'd spend $13.59/month with Mistral Small 3.1 24B vs $15.00/month with GPT-3.5 Turbo (batch) - a $1.41 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. Mistral Small 3.1 24B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (128K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.55/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
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
GPT-3.5 Turbo (batch) and Mistral Small 3.1 24B 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.
By Use Case
Best for Quality
GPT-3.5 Turbo (batch)
Marginally better benchmark scores; both are excellent
Best for Cost
Mistral Small 3.1 24B
9% lower pricing; better value at scale
Best for Reliability
GPT-3.5 Turbo (batch)
Higher uptime and faster response speeds
Best for Prototyping
GPT-3.5 Turbo (batch)
Stronger community support and better developer experience
Best for Production
GPT-3.5 Turbo (batch)
Wider enterprise adoption and proven at scale
by OpenAI
- Choose for Quality - Marginally better benchmark scores; both are excellent
- Choose for Reliability - Higher uptime and faster response speeds
- Choose for Prototyping - Stronger community support and better developer experience
- Choose for Production - Wider enterprise adoption and proven at scale
| Capability | GPT-3.5 Turbo (batch) | Mistral Small 3.1 24B |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
GPT-3.5 Turbo (batch)
OpenAI
Mistral Small 3.1 24B
Mistral AI
Mistral Small 3.1 24B saves you $0.0522/month
That's 4% cheaper than GPT-3.5 Turbo (batch) 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 (batch) | Mistral Small 3.1 24B |
|---|---|---|
| Context Window | 16K | 128K |
| Max Output Tokens | 4,096 | 128,000 |
| Open Source | No | Yes |
| Created | May 28, 2023 | Mar 17, 2025 |