| Signal | GPT-5 Chat | Delta | Qwen3.5-122B-A10B |
|---|---|---|---|
Capabilities | 67 | -17 | |
Benchmarks | 70 | +1 | |
Pricing | 10 | +8 | |
Context window size | 81 | -5 | |
Recency | 90 | -10 | |
Output Capacity | 70 | -10 | |
| Overall Result | 2 wins | of 6 | 4 wins |
8
days higher
3
days
19
days higher
OpenAI
Alibaba
Qwen3.5-122B-A10B saves you $495.00/month
That's $5940.00/year compared to GPT-5 Chat at your current usage level of 100K calls/month.
| Metric | GPT-5 Chat | Qwen3.5-122B-A10B | Winner |
|---|---|---|---|
| Overall Score | 71 | 70 | GPT-5 Chat |
| Rank | #56 | #57 | GPT-5 Chat |
| Quality Rank | #56 | #57 | GPT-5 Chat |
| Adoption Rank | #56 | #57 | GPT-5 Chat |
| Parameters | -- | 122B | -- |
| Context Window | 128K | 262K | Qwen3.5-122B-A10B |
| Pricing | $1.25/$10.00/M | $0.26/$2.08/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 83 | Qwen3.5-122B-A10B |
| Benchmarks | 70 | 69 | GPT-5 Chat |
| Pricing | 10 | 2 | GPT-5 Chat |
| Context window size | 81 | 86 | Qwen3.5-122B-A10B |
| Recency | 90 | 100 | Qwen3.5-122B-A10B |
| Output Capacity | 70 | 80 | Qwen3.5-122B-A10B |
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%). Here's what the scores mean for these two models:
Scores 71/100 (rank #56), placing it in the top 81% of all 290 models tracked.
Scores 70/100 (rank #57), placing it in the top 81% 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 79% better value per quality point. At 1M tokens/day, you'd spend $35.10/month with Qwen3.5-122B-A10B vs $168.75/month with GPT-5 Chat - a $133.65 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 (71/100) 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 Chat and Qwen3.5-122B-A10B are extremely close in overall performance (only 0.09999999999999432 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-5 Chat
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3.5-122B-A10B
79% lower pricing; better value at scale
Best for Reliability
GPT-5 Chat
Higher uptime and faster response speeds
Best for Prototyping
GPT-5 Chat
Stronger community support and better developer experience
Best for Production
GPT-5 Chat
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5 Chat | Qwen3.5-122B-A10B |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Alibaba
Qwen3.5-122B-A10B saves you $11.29/month
That's 79% cheaper than GPT-5 Chat 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 Chat | Qwen3.5-122B-A10B |
|---|---|---|
| Context Window | 128K | 262K |
| Max Output Tokens | 16,384 | 65,536 |
| Open Source | No | Yes |
| Created | Aug 7, 2025 | Feb 25, 2026 |
GPT-5 Chat scores 71/100 (rank #56) compared to Qwen3.5-122B-A10B's 70/100 (rank #57), giving it a 0-point advantage. GPT-5 Chat is the stronger overall choice, though Qwen3.5-122B-A10B may excel in specific areas like cost efficiency.
GPT-5 Chat is ranked #56 and Qwen3.5-122B-A10B is ranked #57 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Qwen3.5-122B-A10B is cheaper at $2.08/M output tokens vs GPT-5 Chat's $10.00/M output tokens - 4.8x more expensive. Input token pricing: GPT-5 Chat at $1.25/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 GPT-5 Chat's 128,000 tokens. A larger context window means the model can process longer documents and conversations.