Claude Opus 4.8 (batch) vs Voxtral Small 24B 2507
| Signal | Claude Opus 4.8 (batch) | Delta | Voxtral Small 24B 2507 |
|---|---|---|---|
Capabilities | 100 | +50 | |
Benchmarks | 93 | +93 | |
Pricing | 88 | -12 | |
Context window size | 95 | +24 | |
Recency | 100 | +19 | |
Output Capacity | 85 | +65 | |
| Overall Result | 5 wins | of 6 | 1 wins |
Score History
94.6
current score
Claude Opus 4.8 (batch)
right now
40
current score
Claude Opus 4.8 (batch)
Anthropic
Voxtral Small 24B 2507
Mistral AI
Voxtral Small 24B 2507 saves you $850.00/month
That's $10200.00/year compared to Claude Opus 4.8 (batch) at your current usage level of 100K calls/month.
| Metric | Claude Opus 4.8 (batch) | Voxtral Small 24B 2507 | Winner |
|---|---|---|---|
| Overall Score | 95 | 40 | Claude Opus 4.8 (batch) |
| Rank | #10 | #307 | Claude Opus 4.8 (batch) |
| Quality Rank | #10 | #307 | Claude Opus 4.8 (batch) |
| Adoption Rank | #10 | #307 | Claude Opus 4.8 (batch) |
| Parameters | -- | 24B | -- |
| Context Window | 1000K | 32K | Claude Opus 4.8 (batch) |
| Pricing | $2.50/$12.50/M | $0.10/$0.30/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 50 | Claude Opus 4.8 (batch) |
| Benchmarks | 93 | -- | Claude Opus 4.8 (batch) |
| Pricing | 88 | 100 | Voxtral Small 24B 2507 |
| Context window size | 95 | 72 | Claude Opus 4.8 (batch) |
| Recency | 100 | 81 | Claude Opus 4.8 (batch) |
| Output Capacity | 85 | 20 | Claude Opus 4.8 (batch) |
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 95/100 (rank #10), placing it in the top 97% of all 290 models tracked.
Scores 40/100 (rank #307), placing it in the top -6% of all 290 models tracked.
Claude Opus 4.8 (batch) has a 55-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Choose Claude Opus 4.8 (batch) when you need:
- Processing long documents or large codebases (1000K token context)
- Multimodal workflows that require image understanding
- Step-by-step reasoning and chain-of-thought problem solving
Choose Voxtral Small 24B 2507 when you need:
- High-volume production workloads where API costs must be minimized
- Self-hosted deployments where you need full control over the model
Voxtral Small 24B 2507 offers 97% better value per quality point. At 1M tokens/day, you'd spend $6.00/month with Voxtral Small 24B 2507 vs $225.00/month with Claude Opus 4.8 (batch) - a $219.00 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. Voxtral Small 24B 2507 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1000K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.30/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (95/100) 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
Claude Opus 4.8 (batch) clearly outperforms Voxtral Small 24B 2507 with a significant 54.599999999999994-point lead. For most general use cases, Claude Opus 4.8 (batch) is the stronger choice. However, Voxtral Small 24B 2507 may still excel in niche scenarios.
By Use Case
Best for Quality
Claude Opus 4.8 (batch)
Marginally better benchmark scores; both are excellent
Best for Cost
Voxtral Small 24B 2507
97% lower pricing; better value at scale
Best for Reliability
Claude Opus 4.8 (batch)
Higher uptime and faster response speeds
Best for Prototyping
Claude Opus 4.8 (batch)
Stronger community support and better developer experience
Best for Production
Claude Opus 4.8 (batch)
Wider enterprise adoption and proven at scale
by Anthropic
- 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 | Claude Opus 4.8 (batch) | Voxtral Small 24B 2507 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
Claude Opus 4.8 (batch)
Anthropic
Voxtral Small 24B 2507
Mistral AI
Voxtral Small 24B 2507 saves you $18.96/month
That's 97% cheaper than Claude Opus 4.8 (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 | Claude Opus 4.8 (batch) | Voxtral Small 24B 2507 |
|---|---|---|
| Context Window | 1M | 32K |
| Max Output Tokens | 128,000 | -- |
| Open Source | No | Yes |
| Created | May 27, 2026 | Oct 30, 2025 |