openai.gpt-oss-safeguard-20b
bedrock_converse · chat model
openai.gpt-oss-safeguard-20b is listed here as a chat model from bedrock_converse. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.
Quick read
Best for
Use this page when you need a fast view of cost, context size, and supported features before testing the model in your own workload.
Things to verify
Always check the provider page for discounts, cache pricing, region rules, and any model limits that may not appear in public metadata.
Pricing
| Item | Price |
|---|---|
| Input | $0.0700 / 1M tokens |
| Output | $0.2000 / 1M tokens |
| Embedding | $0.0700 / 1M tokens |
Token limits
Capabilities
| Capability | Supported |
|---|---|
| Vision | — |
| Function calling | — |
| Parallel function calling | — |
| Tool choice | — |
| Prompt caching | — |
| Reasoning | — |
| Response schema | — |
| System messages | ✅ |
| Audio input | — |
| Audio output | — |
| Web search | — |
| PDF input | — |
| Video input | — |
Benchmarks
Most benchmark rows are attached to the base model family rather than this provider route. Open benchmark explorer
| Benchmark | Score | Metric | Scope | Checked | Source |
|---|---|---|---|---|---|
| AIME 2025 (no tools) | 92.5% | Accuracy (%) | Base model: gpt-oss (gpt-oss-120b) | 2026-05-31 | Link |
| AIME 2025 (no tools) | 91.7% | Accuracy (%) | Base model: gpt-oss (gpt-oss-20b) | 2026-05-31 | Link |
| GPQA Diamond | 80.1% | Accuracy (%) | Base model: gpt-oss (gpt-oss-120b) | 2026-05-31 | Link |
| GPQA Diamond | 71.5% | Accuracy (%) | Base model: gpt-oss (gpt-oss-20b) | 2026-05-31 | Link |
| MMLU | 90.0% | Accuracy (%) | Base model: gpt-oss (gpt-oss-120b) | 2026-05-31 | Link |
| MMLU | 85.3% | Accuracy (%) | Base model: gpt-oss (gpt-oss-20b) | 2026-05-31 | Link |
| SWE-bench Verified | 62.4% | Accuracy (%) | Base model: gpt-oss (gpt-oss-120b) | 2026-05-31 | Link |
| SWE-bench Verified | 60.7% | Accuracy (%) | Base model: gpt-oss (gpt-oss-20b) | 2026-05-31 | Link |
| Codeforces (with tools) | 2622 | Elo | Base model: gpt-oss (gpt-oss-120b) | 2026-05-31 | Link |
| Codeforces (with tools) | 2516 | Elo | Base model: gpt-oss (gpt-oss-20b) | 2026-05-31 | Link |
| HealthBench | 57.6% | Score (%) | Base model: gpt-oss (gpt-oss-120b) | 2026-05-31 | Link |
| HealthBench | 42.5% | Score (%) | Base model: gpt-oss (gpt-oss-20b) | 2026-05-31 | Link |
| Artificial Analysis Intelligence Index | 24.5 | score | Base model: gpt-oss (openai/gpt-oss-20b:free) | 2026-05-31 | Link |
| Artificial Analysis Coding Index | 18.5 | score | Base model: gpt-oss (openai/gpt-oss-20b:free) | 2026-05-31 | Link |
| Artificial Analysis Agentic Index | 27.6 | score | Base model: gpt-oss (openai/gpt-oss-20b:free) | 2026-05-31 | Link |
| GPQA Diamond | 68.8% | accuracy | Base model: gpt-oss (openai/gpt-oss-20b:free) | 2026-05-31 | Link |
| Humanity's Last Exam | 9.8% | accuracy | Base model: gpt-oss (openai/gpt-oss-20b:free) | 2026-05-31 | Link |
| IFBench | 65.1% | accuracy | Base model: gpt-oss (openai/gpt-oss-20b:free) | 2026-05-31 | Link |
| SciCode | 34.4% | accuracy | Base model: gpt-oss (openai/gpt-oss-20b:free) | 2026-05-31 | Link |
| Terminal-Bench Hard | 10.6% | accuracy | Base model: gpt-oss (openai/gpt-oss-20b:free) | 2026-05-31 | Link |
| Artificial Analysis Intelligence Index | 33.3 | score | Base model: gpt-oss (openai/gpt-oss-120b) | 2026-05-31 | Link |
| Artificial Analysis Coding Index | 28.6 | score | Base model: gpt-oss (openai/gpt-oss-120b) | 2026-05-31 | Link |
| Artificial Analysis Agentic Index | 37.9 | score | Base model: gpt-oss (openai/gpt-oss-120b) | 2026-05-31 | Link |
Sources
| Source links | |
| Pricing data | LiteLLM model cost map |
| Synced at | 2026-05-28 |
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