| Signal | GPT-5.3-Codex | Delta | Qwen3.5-Flash |
|---|---|---|---|
Capabilities | 100 | +17 | |
Benchmarks | 88 | +21 | |
Pricing | 86 | -14 | |
Context window size | 89 | -6 | |
Recency | 100 | -- | |
Output Capacity | 85 | +5 | |
| Overall Result | 3 wins | of 6 | 2 wins |
Score History
88.7
current score
GPT-5.3-Codex
right now
68.7
current score
OpenAI
Alibaba
Qwen3.5-Flash saves you $855.50/month
That's $10266.00/year compared to GPT-5.3-Codex at your current usage level of 100K calls/month.
| Metric | GPT-5.3-Codex | Qwen3.5-Flash | Winner |
|---|---|---|---|
| Overall Score | 89 | 69 | GPT-5.3-Codex |
| Rank | #9 | #109 | GPT-5.3-Codex |
| Quality Rank | #9 | #109 | GPT-5.3-Codex |
| Adoption Rank | #9 | #109 | GPT-5.3-Codex |
| Parameters | -- | -- | -- |
| Context Window | 400K | 1000K | Qwen3.5-Flash |
| Pricing | $1.75/$14.00/M | $0.07/$0.26/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 83 | GPT-5.3-Codex |
| Benchmarks | 88 | 66 | GPT-5.3-Codex |
| Pricing | 86 | 100 | Qwen3.5-Flash |
| Context window size | 89 | 95 | Qwen3.5-Flash |
| Recency | 100 | 100 | GPT-5.3-Codex |
| Output Capacity | 85 | 80 | GPT-5.3-Codex |
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 89/100 (rank #9), placing it in the top 97% of all 290 models tracked.
Scores 69/100 (rank #109), placing it in the top 63% of all 290 models tracked.
GPT-5.3-Codex has a 20-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Qwen3.5-Flash offers 98% better value per quality point. At 1M tokens/day, you'd spend $4.88/month with Qwen3.5-Flash vs $236.25/month with GPT-5.3-Codex - a $231.38 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. Qwen3.5-Flash 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 ($0.26/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (89/100) 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-5.3-Codex clearly outperforms Qwen3.5-Flash with a significant 20-point lead. For most general use cases, GPT-5.3-Codex is the stronger choice. However, Qwen3.5-Flash may still excel in niche scenarios.
Best for Quality
GPT-5.3-Codex
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3.5-Flash
98% lower pricing; better value at scale
Best for Reliability
GPT-5.3-Codex
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.3-Codex
Stronger community support and better developer experience
Best for Production
GPT-5.3-Codex
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.3-Codex | Qwen3.5-Flash |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Alibaba
Qwen3.5-Flash saves you $19.52/month
That's 98% cheaper than GPT-5.3-Codex 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-5.3-Codex | Qwen3.5-Flash |
|---|---|---|
| Context Window | 400K | 1M |
| Max Output Tokens | 128,000 | 65,536 |
| Open Source | No | No |
| Created | Feb 24, 2026 | Feb 25, 2026 |