| Signal | Claude Sonnet 4 | Delta | Qwen3.5-122B-A10B |
|---|---|---|---|
Capabilities | 83 | -- | |
Benchmarks | 79 | +10 | |
Pricing | 15 | +13 | |
Context window size | 84 | -2 | |
Recency | 77 | -23 | |
Output Capacity | 80 | 0 | |
| Overall Result | 2 wins | of 6 | 3 wins |
9
days ranked higher
3
days
18
days ranked higher
Anthropic
Alibaba
Qwen3.5-122B-A10B saves you $920.00/month
That's $11040.00/year compared to Claude Sonnet 4 at your current usage level of 100K calls/month.
| Metric | Claude Sonnet 4 | Qwen3.5-122B-A10B | Winner |
|---|---|---|---|
| Overall Score | 80 | 80 | -- |
| Rank | #78 | #77 | Qwen3.5-122B-A10B |
| Quality Rank | #78 | #77 | Qwen3.5-122B-A10B |
| Adoption Rank | #78 | #77 | Qwen3.5-122B-A10B |
| Parameters | -- | 122B | -- |
| Context Window | 200K | 262K | Qwen3.5-122B-A10B |
| Pricing | $3.00/$15.00/M | $0.26/$2.08/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 83 | Claude Sonnet 4 |
| Benchmarks | 79 | 69 | Claude Sonnet 4 |
| Pricing | 15 | 2 | Claude Sonnet 4 |
| Context window size | 84 | 86 | Qwen3.5-122B-A10B |
| Recency | 77 | 100 | Qwen3.5-122B-A10B |
| Output Capacity | 80 | 80 | Qwen3.5-122B-A10B |
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 80/100 (rank #78), placing it in the top 73% of all 290 models tracked.
Scores 80/100 (rank #77), placing it in the top 74% 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.
Qwen3.5-122B-A10B offers 87% better value per quality point. At 1M tokens/day, you'd spend $35.10/month with Qwen3.5-122B-A10B vs $270.00/month with Claude Sonnet 4 - a $234.90 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. Qwen3.5-122B-A10B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (262K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($2.08/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (80/100) 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 Sonnet 4 and Qwen3.5-122B-A10B 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
Claude Sonnet 4
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3.5-122B-A10B
87% lower pricing; better value at scale
Best for Reliability
Claude Sonnet 4
Higher uptime and faster response speeds
Best for Prototyping
Claude Sonnet 4
Stronger community support and better developer experience
Best for Production
Claude Sonnet 4
Wider enterprise adoption and proven at scale
by Anthropic
| Capability | Claude Sonnet 4 | Qwen3.5-122B-A10B |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
Anthropic
Alibaba
Qwen3.5-122B-A10B saves you $20.44/month
That's 87% cheaper than Claude Sonnet 4 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 Sonnet 4 | Qwen3.5-122B-A10B |
|---|---|---|
| Context Window | 200K | 262K |
| Max Output Tokens | 64,000 | 65,536 |
| Open Source | No | Yes |
| Created | May 22, 2025 | Feb 25, 2026 |
Both Claude Sonnet 4 and Qwen3.5-122B-A10B score 80/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
Claude Sonnet 4 is ranked #78 and Qwen3.5-122B-A10B is ranked #77 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.
Qwen3.5-122B-A10B is cheaper at $2.08/M output tokens vs Claude Sonnet 4's $15.00/M output tokens - 7.2x more expensive. Input token pricing: Claude Sonnet 4 at $3.00/M vs Qwen3.5-122B-A10B at $0.26/M.
Qwen3.5-122B-A10B has a larger context window of 262,144 tokens compared to Claude Sonnet 4's 200,000 tokens. A larger context window means the model can process longer documents and conversations.