Model decision surface
Compare AI models
Start with gpt-oss-120b and Qwen3 32B, or choose any two current ranked language models. Compare capability evidence, price, context, provider availability, and weight access without pretending one field decides every use case.
Current public data
gpt-oss-120b vs Qwen3 32B
Live dataset updated 9/15/2026, 8:34:26 PM UTC
Open 1200×630 evidence receipt| Field | gpt-oss-120b OpenAI | Qwen3 32B Qwen |
|---|---|---|
| ModelCap position | #130 | #135 |
| Index score | 36.4 | 34.5 |
| Evidence | Measured3 public benchmark observations across 3 boards | Measured2 public benchmark observations across 2 boards |
| Input / 1M | $0.037 | $0.08 |
| Output / 1M | $0.17 | $0.28 |
| Pricing status | fresh | fresh |
| Context | 131K | 131K |
| Providers | 20 | 2 |
| Weight access | Open weights | Open weights |
Decision facts
- gpt-oss-120b is #130; Qwen3 32B is #135 on the same current language board.
- Index scores are 36.4 for gpt-oss-120b and 34.5 for Qwen3 32B. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Both positions use Measured evidence.
- Listed output price per 1M tokens is $0.17 for gpt-oss-120b and $0.28 for Qwen3 32B. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.16 for gpt-oss-120b versus $0.30 for Qwen3 32B. gpt-oss-120b costs 47.0% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.
- Published context is 131,072 tokens for gpt-oss-120b and 131,072 for Qwen3 32B.
- ModelCap currently lists 20 providers for gpt-oss-120b and 2 for Qwen3 32B.
These are separate published fields, not a synthetic winner. ModelCap does not collapse price, access, context, and capability evidence into a hidden recommendation score.
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Each comparison page is a permanent, shareable URL with the same live figures as this tool: ModelCap Index position, API pricing, context window, provider count, weight access and every shared benchmark board.