| Signal | GPT-5 | Delta | Mistral Small 3.2 24B |
|---|---|---|---|
Capabilities | 100 | +33 | |
Benchmarks | 88 | +88 | |
Pricing | 10 | +10 | |
Context window size | 89 | +8 | |
Recency | 91 | +9 | |
Output Capacity | 85 | +65 | |
| Overall Result | 6 wins | of 6 | 0 wins |
30
days ranked higher
0
days
0
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OpenAI
Mistral AI
Mistral Small 3.2 24B saves you $607.50/month
That's $7290.00/year compared to GPT-5 at your current usage level of 100K calls/month.
| Metric | GPT-5 | Mistral Small 3.2 24B | Winner |
|---|---|---|---|
| Overall Score | 90 | 67 | GPT-5 |
| Rank | #11 | #171 | GPT-5 |
| Quality Rank | #11 | #171 | GPT-5 |
| Adoption Rank | #11 | #171 | GPT-5 |
| Parameters | -- | 24B | -- |
| Context Window | 400K | 128K | GPT-5 |
| Pricing | $1.25/$10.00/M | $0.07/$0.20/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 67 | GPT-5 |
| Benchmarks | 88 | -- | GPT-5 |
| Pricing | 10 | 0 | GPT-5 |
| Context window size | 89 | 81 | GPT-5 |
| Recency | 91 | 83 | GPT-5 |
| Output Capacity | 85 | 20 | GPT-5 |
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 90/100 (rank #11), placing it in the top 97% of all 290 models tracked.
Scores 67/100 (rank #171), placing it in the top 41% of all 290 models tracked.
GPT-5 has a 23-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Mistral Small 3.2 24B offers 98% better value per quality point. At 1M tokens/day, you'd spend $4.13/month with Mistral Small 3.2 24B vs $168.75/month with GPT-5 - a $164.63 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. Mistral Small 3.2 24B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (400K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.20/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (90/100) 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-5 clearly outperforms Mistral Small 3.2 24B with a significant 22.799999999999997-point lead. For most general use cases, GPT-5 is the stronger choice. However, Mistral Small 3.2 24B may still excel in niche scenarios.
Best for Quality
GPT-5
Marginally better benchmark scores; both are excellent
Best for Cost
Mistral Small 3.2 24B
98% lower pricing; better value at scale
Best for Reliability
GPT-5
Higher uptime and faster response speeds
Best for Prototyping
GPT-5
Stronger community support and better developer experience
Best for Production
GPT-5
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5 | Mistral Small 3.2 24B |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Mistral AI
Mistral Small 3.2 24B saves you $13.88/month
That's 97% cheaper than GPT-5 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-5 | Mistral Small 3.2 24B |
|---|---|---|
| Context Window | 400K | 128K |
| Max Output Tokens | 128,000 | -- |
| Open Source | No | Yes |
| Created | Aug 7, 2025 | Jun 20, 2025 |
GPT-5 scores 90/100 (rank #11) compared to Mistral Small 3.2 24B's 67/100 (rank #171), giving it a 23-point advantage. GPT-5 is the stronger overall choice, though Mistral Small 3.2 24B may excel in specific areas like cost efficiency.
GPT-5 is ranked #11 and Mistral Small 3.2 24B is ranked #171 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.
Mistral Small 3.2 24B is cheaper at $0.20/M output tokens vs GPT-5's $10.00/M output tokens - 50.0x more expensive. Input token pricing: GPT-5 at $1.25/M vs Mistral Small 3.2 24B at $0.07/M.
GPT-5 has a larger context window of 400,000 tokens compared to Mistral Small 3.2 24B's 128,000 tokens. A larger context window means the model can process longer documents and conversations.