GPT-5.2 Pro vs Qwen3 Max
GPT-5.2 Pro and Qwen3 Max sit at opposite ends of the cost spectrum. GPT-5.2 Pro is OpenAI's December 2025 flagship, built for agentic coding and long-context reasoning with mandatory reasoning modes. Qwen3 Max is Qwen's September 2025 release, text-only, no forced reasoning overhead, and priced for scale. Both are available on OpenKey through one API key with a flat 3% fee over provider list price — the question is whether GPT-5.2 Pro's extra capability justifies its cost for your workload.
Spec vs spec
| Spec | GPT-5.2 Pro | Qwen3 Max |
|---|---|---|
| Context window | 400K | 262K |
| Max output | 128K | 33K |
| Input modalities | image, text, file | text |
| Output modalities | text | text |
| Knowledge cutoff | — | Jun 30, 2025 |
| Released | Dec 10, 2025 | Sep 23, 2025 |
| Reasoning | always on | optional |
Pricing
Per 1M tokens. Provider price plus the flat 3% fee — the sum is what you pay.
openai/gpt-5.2-pro
Input · 1M tokens
$21.00 + 3%$21.63
Output · 1M tokens
$168.00 + 3%$173.04
FEE — FLAT, EVERY MODEL3%
qwen/qwen3-max
Input · 1M tokens
$0.780 + 3%$0.803
Output · 1M tokens
$3.90 + 3%$4.02
Cache read · 1M tokens
$0.156 + 3%$0.161
Cache write · 1M tokens
$0.975 + 3%$1.00
FEE — FLAT, EVERY MODEL3%
One workload, priced on both
10M input + 2M output tokens at each model's price, flat 3% fee included.
openai/gpt-5.2-pro
$562.38
$546.00 provider + 3%
qwen/qwen3-maxCheaper
$16.07
$15.60 provider + 3%
Pricing math
GPT-5.2 Pro costs $21.00/M input and $168.00/M output at the provider; on OpenKey that's $21.63/M input ($21.00 × 1.03) and $173.04/M output ($168.00 × 1.03). Qwen3 Max is $0.78/M input and $3.90/M output provider-side, or $0.8034/M and $4.017/M on OpenKey — same 3% math.
Run the numbers on a 10M-input / 2M-output workload: GPT-5.2 Pro costs $546.00, Qwen3 Max costs $15.60. That's a 26.92x gap on input pricing alone. If you're processing volume — batch summarization, classification, RAG pipelines — Qwen3 Max wins on cost by a wide margin. GPT-5.2 Pro only makes sense per-request when the task genuinely needs its extra reasoning depth or multimodal input.
Context and output limits
GPT-5.2 Pro supports a 400,000-token context window and up to 128,000 tokens of output. Qwen3 Max supports 262,144 tokens of context and caps output at 32,768 tokens — a 1.53x context ratio in GPT-5.2 Pro's favor, and a 4x gap on max output.
For long-document work — ingesting large codebases, legal contracts, or multi-file diffs — the extra context headroom on GPT-5.2 Pro matters if you're near Qwen3 Max's ceiling. But most real workloads don't fill 262K tokens, so this is only decisive at the extremes.
Modality and reasoning
GPT-5.2 Pro accepts text, image, and file input and outputs text; Qwen3 Max is text-in, text-out only. If your pipeline needs to read screenshots, PDFs, or diagrams, Qwen3 Max is disqualified outright.
GPT-5.2 Pro also has mandatory reasoning — you can't turn it off, and it supports xhigh, high, and medium effort levels (default medium). That's useful for hard multi-step problems but adds latency and cost you can't opt out of. Qwen3 Max has no mandatory reasoning step, which keeps it faster and cheaper for straightforward completions, though it also supports more classic sampling controls like temperature, top_p, and logprobs — parameters GPT-5.2 Pro doesn't expose.
When to pick each
Pick GPT-5.2 Pro when the task involves images or files, when you need output beyond 32K tokens, or when the problem is hard enough to justify mandatory step-by-step reasoning at high effort. Pick Qwen3 Max for high-volume text tasks, multilingual work, or any pipeline where the 26.92x price difference compounds fast across millions of calls. Qwen3 Max also has published Design Arena benchmark data (across categories like codecategories, gamedev, and dataviz) if you want category-level signal before committing; GPT-5.2 Pro has no benchmarks published in this dataset, so its edge on hard reasoning tasks is architectural, not yet independently scored here.
Which model for which job
| Use case | Pick | Why |
|---|---|---|
| High-volume text classification | Qwen3 Max | $15.60 vs $546.00 for the same 10M-in/2M-out workload |
| Image or PDF understanding | GPT-5.2 Pro | Only GPT-5.2 Pro accepts image and file input |
| Very long output generation | GPT-5.2 Pro | 128,000 max output tokens vs 32,768 for Qwen3 Max |
| Multilingual or long-tail knowledge queries | Qwen3 Max | Built specifically for multilingual support and long-tail knowledge coverage |
| Budget-constrained agentic coding pipelines | Qwen3 Max | 27x cheaper input pricing keeps iterative agent loops affordable |
| Maximum context window for huge documents | GPT-5.2 Pro | 400,000 tokens vs 262,144, a 1.53x ratio |
Questions
- How much more expensive is GPT-5.2 Pro than Qwen3 Max?
- On input tokens, GPT-5.2 Pro is 26.92x more expensive ($21.63/M vs $0.8034/M on OpenKey). For a 10M-input/2M-output workload, GPT-5.2 Pro costs $546.00 total versus $15.60 for Qwen3 Max — a difference that scales linearly with volume.
- Which model has a bigger context window?
- GPT-5.2 Pro supports 400,000 tokens of context versus Qwen3 Max's 262,144 tokens, a 1.53x ratio. GPT-5.2 Pro also allows up to 128,000 tokens of output compared to Qwen3 Max's 32,768 cap.
- Can Qwen3 Max handle images or files?
- No. Qwen3 Max is text-to-text only. GPT-5.2 Pro accepts text, image, and file inputs, making it the only option here for multimodal workloads.
- Does GPT-5.2 Pro let you disable reasoning?
- No, reasoning is mandatory on GPT-5.2 Pro, with effort levels of xhigh, high, or medium (default medium). Qwen3 Max has no mandatory reasoning step, which keeps latency and cost lower for simple completions.