GPT OSS 120BvsQwen3 235B A22B
GPT OSS 120B has a larger context window than Qwen3 235B A22B (131K tokens vs 33K tokens).
| Spec | GPT OSS 120B | Qwen3 235B A22B |
|---|---|---|
| Input price | $0.18/M tokens | — |
| Output price | $0.8/M tokens | — |
| Context window | 131K tokens | 33K tokens |
| Parameters | 117B (5.1B active) | 235B (22B Active) |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Aug 2025 | Apr 2025 |
| Codeforces | Outperforms o3-mini | Competitive with o3-mini/Gemini 2.5 Pro |
Our Verdict
GPT OSS 120B
Qwen3 235B A22BRunner-up
Not enough votes to call it. On the specs, GPT OSS 120B has the edge: newer, bigger context window, major provider backing.
Too close to call
API pricing
Cost per 1M tokens
GPT OSS 120B
Input
$0.18
Output
$0.80
Qwen3 235B A22B
Input
—
Output
—
Where to run it
19 hosts, cheapest first
GPT OSS 120B18 hosts
AkashMLbf16$0.03 in$0.17 out131k99.9% upCoreWeavefp4$0.03 in$0.17 out131k99.9% upDeepInfrabf16$0.04 in$0.17 out131k99.4% upDigitalOcean$0.06 in$0.39 out128k99.7% upMancerfp8$0.06 in$0.50 out131k99.6% upGoogle Vertex AI$0.09 in$0.36 out131k99.9% up
12 more hostsFewer hosts
Basetenfp4$0.10 in$0.50 out128k100% upParasailfp4$0.10 in$0.75 out131k100% upSambaNova$0.14 in$0.95 out131k96.9% upAmazon Bedrock$0.15 in$0.60 out131k98.1% upGroq$0.15 in$0.60 out131k100% upNebiusfp4$0.15 in$0.60 out131k96.2% upTogether$0.15 in$0.60 out131k98.8% upCerebrasfp16$0.35 in$0.75 out131k100% upNovitafp4degraded$0.05 in$0.25 out131k86.7% upSiliconFlowfp8degraded$0.05 in$0.45 out131k84.3% upPhaladegraded$0.15 in$0.60 out131k88.8% upMaradegraded$0.15 in$0.75 out131k86% up
Qwen3 235B A22B1 host
Per million tokens. Prices and uptime via OpenRouter, checked 9 Sep 2026.
Writing DNA
Style Comparison
Similarity
68%
Qwen3 235B A22B uses 2.3x more lists
GPT OSS 120B
Qwen3 235B A22B
52%Vocabulary59%
19wSentence Length16w
0.28Hedging0.58
7.4Bold7.0
1.8Lists4.1
0.15Emoji0.33
0.73Headings0.88
0.17Transitions0.14
Based on 21 + 27 text responses
Research
What we learned reading every model
FAQ
Common questions
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