GPT-5 vs Qwen3-Max
GPT-5 (2025) and Qwen3-Max (2025) are frontier reasoning models from OpenAI and Alibaba. GPT-5 ships a 400k-token context window, while Qwen3-Max ships a 262k-token context window. On SWE-bench Verified, Qwen3-Max leads by 3.9 pts. On pricing, GPT-5 costs $1.25/1M input tokens; Qwen3-Max ranges from $1.20 to $3/1M input tokens by tier. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
GPT-5 is safer overall; choose Qwen3-Max when vision-heavy evaluation matters.
Decision scorecard
Local evidence first| Signal | GPT-5 | Qwen3-Max |
|---|---|---|
| Best for | reasoning-heavy apps, multimodal apps, and tool-calling agents | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 400k | 262k |
| Cheapest output | $10/1M tokens | $3.90/1M tokens |
| Provider routes | 4 tracked | 3 tracked |
| Shared benchmarks | 1 rows | SWE-bench Verified leader |
Decision tradeoffs
- GPT-5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GPT-5 has broader tracked provider coverage for fallback and procurement flexibility.
- GPT-5 uniquely exposes Reasoning and Code execution in local model data.
- Local decision data tags GPT-5 for Coding, RAG, and Agents.
- Qwen3-Max leads the largest shared benchmark signal on SWE-bench Verified by 3.9 points.
- Qwen3-Max has the lower cheapest tracked output price at $3.90/1M tokens.
- Local decision data tags Qwen3-Max for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
GPT-5
$3,500
Cheapest tracked route/tier: Replicate API
Qwen3-Max
$1,599
Cheapest tracked route/tier: OpenRouter
Estimated monthly gap: $1,901. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- Qwen3-Max is $6.10/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Reasoning and Code execution before moving production traffic.
- Provider overlap exists on OpenRouter and Vercel AI Gateway; start route-level A/B tests there.
- GPT-5 is $6.10/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- GPT-5 adds Reasoning and Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-08-07 | 2025-04-28 |
| Context window | 400k | 262k |
| Parameters | — | — |
| Architecture | decoder only | decoder only |
| License | Proprietary | Apache 2.0(OSI) |
| Openness | Proprietary | Open source |
| Commercial use | Commercial use with conditions | Commercial use allowed |
| Knowledge cutoff | 2024-09 | 2025-12 |
Pricing and availability
| Pricing attribute | GPT-5 | Qwen3-Max |
|---|---|---|
| Input price | $1.25/1M tokens |
|
| Output price | $10/1M tokens |
|
| Providers |
Capabilities
| Capability | GPT-5 | Qwen3-Max |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | Yes | No |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | GPT-5 | Qwen3-Max |
|---|---|---|
| SWE-bench Verified | 74.9 | 78.8 |
Deep dive
On shared benchmark coverage, SWE-bench Verified has GPT-5 at 74.9 and Qwen3-Max at 78.8, with Qwen3-Max ahead by 3.9 points. The largest visible gap is 3.9 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 reasoning mode: GPT-5 and code execution: GPT-5. Both models share vision, 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.
For cost, GPT-5 lists $1.25/1M input and $10/1M output tokens on the cheapest tracked provider, while Qwen3-Max lists tiered pricing: 0-32,001t is $1.20/1M input and $6/1M output; 0-128,001t is $2.40/1M input and $12/1M output; 128,001t+ is $3/1M input and $15/1M output. A 70/30 input-output blend puts Qwen3-Max lower by about $2.16 per million blended tokens. For tiered rows, this cheapest-track view can understate interactive or fast-lane spend, so compare the tier you will actually use. Availability is 4 providers versus 3, so concentration risk also matters.
Choose GPT-5 when coding workflow support, larger context windows, and broader provider choice are central to the workload. Choose Qwen3-Max when vision-heavy evaluation and lower cheapest-tier input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, GPT-5 or Qwen3-Max?
GPT-5 supports 400k tokens, while Qwen3-Max supports 262k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, GPT-5 or Qwen3-Max?
GPT-5 lists $1.25/1M input and $10/1M output tokens on the cheapest tracked provider. Qwen3-Max lists tiered pricing: 0-32,001t is $1.20/1M input and $6/1M output; 0-128,001t is $2.40/1M input and $12/1M output; 128,001t+ is $3/1M input and $15/1M output. Compare the tier you will actually use; cheap async pricing can overstate savings for interactive workflows. Provider discounts or batch pricing can still change the final bill.
Is GPT-5 or Qwen3-Max open source?
GPT-5 is listed under Proprietary. Qwen3-Max 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 vision, GPT-5 or Qwen3-Max?
Both GPT-5 and Qwen3-Max expose vision. 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 multimodal input, GPT-5 or Qwen3-Max?
Both GPT-5 and Qwen3-Max 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.
Where can I run GPT-5 and Qwen3-Max?
GPT-5 is available on Replicate API, OpenRouter, OpenAI API, and Vercel AI Gateway. Qwen3-Max is available on OpenRouter, Vercel AI Gateway, and Novita AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.