Model decision surface
Compare AI models
Start with Llama 4 Scout and gpt-oss-safeguard-20b, 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
Llama 4 Scout vs gpt-oss-safeguard-20b
Live dataset updated 9/19/2026, 11:04:59 PM UTC
Open 1200×630 evidence receipt| Field | Llama 4 Scout Meta | gpt-oss-safeguard-20b OpenAI |
|---|---|---|
| ModelCap position | #166 | #164 |
| Index score | 25.8 | 27.0 |
| Evidence | Measured3 public benchmark observations across 3 boards | Inheritedfinetune of openai/gpt-oss-20b · fp4 (100%) |
| Input / 1M | $0.10 | $0.075 |
| Output / 1M | $0.30 | $0.30 |
| Pricing status | fresh | fresh |
| Context | 1.3M | 131K |
| Providers | 3 | 1 |
| Weight access | Gated access | Open weights |
Decision facts
- Llama 4 Scout is #166; gpt-oss-safeguard-20b is #164 on the same current language board.
- Index scores are 25.8 for Llama 4 Scout and 27.0 for gpt-oss-safeguard-20b. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Evidence differs: Llama 4 Scout is Measured; gpt-oss-safeguard-20b is Inherited.
- Listed output price per 1M tokens is $0.30 for Llama 4 Scout and $0.30 for gpt-oss-safeguard-20b. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.35 for Llama 4 Scout versus $0.30 for gpt-oss-safeguard-20b. gpt-oss-safeguard-20b costs 14.3% 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 1,310,720 tokens for Llama 4 Scout and 131,072 for gpt-oss-safeguard-20b.
- Weight access differs: Llama 4 Scout is gated; gpt-oss-safeguard-20b is open.
- ModelCap currently lists 3 providers for Llama 4 Scout and 1 for gpt-oss-safeguard-20b.
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.