GPT-5.3-Codex vs Qwen3.6-35B-A3B
GPT-5.3-Codex (2026) and Qwen3.6-35B-A3B (2026) are agentic coding models from OpenAI and Alibaba. GPT-5.3-Codex ships a not-yet-sourced context window, while Qwen3.6-35B-A3B ships a 262K-token context window. On SWE-bench Verified, GPT-5.3-Codex leads by 11.6 pts. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.
Qwen3.6-35B-A3B is safer overall; choose GPT-5.3-Codex when coding workflow support matters.
Specs
| Released | 2026-02-05 | 2026-04-16 |
| Context window | — | 262K |
| Parameters | — | 35 |
| Architecture | decoder only | moe |
| License | Proprietary | Apache 2.0 |
| Knowledge cutoff | - | - |
Pricing and availability
| GPT-5.3-Codex | Qwen3.6-35B-A3B | |
|---|---|---|
| Input price | $1.75/1M tokens | - |
| Output price | $14/1M tokens | - |
| Providers | - |
Capabilities
| GPT-5.3-Codex | Qwen3.6-35B-A3B | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | GPT-5.3-Codex | Qwen3.6-35B-A3B |
|---|---|---|
| SWE-bench Verified | 85.0 | 73.4 |
| SWE-bench Pro | 56.8 | 49.5 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has GPT-5.3-Codex at 85 and Qwen3.6-35B-A3B at 73.4, with GPT-5.3-Codex ahead by 11.6 points; SWE-bench Pro has GPT-5.3-Codex at 56.8 and Qwen3.6-35B-A3B at 49.5, with GPT-5.3-Codex ahead by 7.3 points. The largest visible gap is 11.6 points on SWE-bench Verified, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on structured outputs: GPT-5.3-Codex and code execution: GPT-5.3-Codex. Both models share multimodal input, function calling, and tool use, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
Pricing coverage is uneven: GPT-5.3-Codex has $1.75/1M input tokens and Qwen3.6-35B-A3B has no token price sourced yet. Provider availability is 1 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.
Choose GPT-5.3-Codex when coding workflow support and broader provider choice are central to the workload. Choose Qwen3.6-35B-A3B when coding workflow support are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Is GPT-5.3-Codex or Qwen3.6-35B-A3B open source?
GPT-5.3-Codex is listed under Proprietary. Qwen3.6-35B-A3B is listed under Apache 2.0. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for multimodal input, GPT-5.3-Codex or Qwen3.6-35B-A3B?
Both GPT-5.3-Codex and Qwen3.6-35B-A3B expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for function calling, GPT-5.3-Codex or Qwen3.6-35B-A3B?
Both GPT-5.3-Codex and Qwen3.6-35B-A3B expose function calling. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for tool use, GPT-5.3-Codex or Qwen3.6-35B-A3B?
Both GPT-5.3-Codex and Qwen3.6-35B-A3B expose tool use. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for structured outputs, GPT-5.3-Codex or Qwen3.6-35B-A3B?
GPT-5.3-Codex has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run GPT-5.3-Codex and Qwen3.6-35B-A3B?
GPT-5.3-Codex is available on OpenRouter. Qwen3.6-35B-A3B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.