GPT-5 Nano vs Qwen3-235B: Detailed Comparison
Choosing between GPT-5 Nano (OpenAI) and
Qwen3-235B (Alibaba) comes down to three things:
per-token pricing, context window, and which capability matters most for your workload.
GPT-5 Nano costs $0.05/M input vs
$0.50/M for Qwen3-235B;
context windows are 400K vs
128K tokens. Detailed breakdown below.
Side-by-side specs
| Spec | GPT-5 Nano | Qwen3-235B |
|---|
| Provider | OpenAI | Alibaba |
|---|
| Released | 2025-08-07 | 2025-04-29 |
|---|
| Input price |
$0.05/M |
$0.50/M |
| Output price |
$0.40/M |
$2.00/M |
| Cached input |
$0.0050/M |
— |
| Context window |
400K |
128K |
| Max output |
64K |
8K |
| Modalities |
text |
text |
| Tokenizer |
o200k_base |
qwen |
Capability matrix
| Capability | GPT-5 Nano | Qwen3-235B |
|---|
| function calling |
Yes |
Yes |
| json mode |
Yes |
Yes |
| streaming |
Yes |
Yes |
| thinking |
No |
Yes |
| tool use |
No |
Yes |
Per-call cost on typical workloads
| Workload (in/out tokens) | GPT-5 Nano | Qwen3-235B | Cheaper by |
|---|
| Standard chat (1K / 500) |
$0.000250 |
$0.001500 |
GPT-5 Nano by $0.001250 |
| RAG (4K / 500) |
$0.000400 |
$0.003000 |
GPT-5 Nano by $0.002600 |
| Long doc (20K / 1K) |
$0.001400 |
$0.012000 |
GPT-5 Nano by $0.010600 |
| Very long context (100K / 2K) |
$0.005600 |
$0.053000 |
GPT-5 Nano by $0.047400 |
When to choose GPT-5 Nano over Qwen3-235B
- Per-token input cost is 90% lower — meaningful for high-volume workloads.
- Larger context window (400K vs 128K) — relevant when whole documents or long histories must fit in a single call.
When to choose Qwen3-235B over GPT-5 Nano
- Supports thinking — GPT-5 Nano does not.
- Supports tool use — GPT-5 Nano does not.
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