gpt-oss-120b
deepinfra · chat model
gpt-oss-120b is listed here as a chat model from deepinfra. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.
Input
$0.0500 / 1M tokens
Output
$0.4500 / 1M tokens
Cached input
N/A
Context
131.1K
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 | $0.0500 / 1M tokens |
| Output | $0.4500 / 1M tokens |
| Embedding | $0.0500 / 1M tokens |
Token limits
Context window
131.1K
Max input tokens
131.1K
Max output tokens
131.1K
Max tokens
131.1K
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 | 97.9% | accuracy (%) | Base model: gpt-oss-120b (gpt-oss-120b) | 2026-05-31 | Link |
| SWE-bench Verified | 62.4% | accuracy (%) | Base model: gpt-oss-120b (gpt-oss-120b) | 2026-05-31 | Link |
| Codeforces | 2622 Elo | Elo | Base model: gpt-oss-120b (gpt-oss-120b) | 2026-05-31 | Link |
| 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 |
Docs
| Official docs |
Similar models
This list is ranked by overall similarity. Use filters to emphasize the lens that matters most for the replacement you are making.
Comparing from
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| gpt-oss-120b deepinfra | In $0.0500 / 1M tokens Out $0.4500 / 1M tokens | text
Output: text | Function callingTool choice | 131.1K | Current model Reference row |
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| Llama-3.3-Nemotron-Super-49B-v1.5 deepinfra | In $0.1000 / 1M tokens Out $0.4000 / 1M tokens | text
Output: text | Function callingTool choice | 131.1K | Same provider Overall 94% |
| Llama-3.3-70B-Instruct-Turbo deepinfra | In $0.1300 / 1M tokens Out $0.3900 / 1M tokens | text
Output: text | Function callingTool choice | 131.1K | Same provider Overall 93% |
| QwQ-32B deepinfra | In $0.1500 / 1M tokens Out $0.4000 / 1M tokens | text
Output: text | Function callingTool choice | 131.1K | Same provider Overall 93% |
| Llama-3.3-70B-Instruct deepinfra | In $0.2300 / 1M tokens Out $0.4000 / 1M tokens | text
Output: text | Function callingTool choice | 131.1K | Same provider Overall 92% |
| grok-3-mini vercel_ai_gateway | In $0.3000 / 1M tokens Out $0.5000 / 1M tokens | text
Output: text | Function callingTool choice | 131.1K | Text covered Overall 91% |
| Meta-Llama-3.1-70B-Instruct-Turbo deepinfra | In $0.1000 / 1M tokens Out $0.2800 / 1M tokens | text
Output: text | Function callingTool choice | 131.1K | Same provider Overall 91% |
| NVIDIA-Nemotron-Nano-9B-v2 deepinfra | In $0.0400 / 1M tokens Out $0.1600 / 1M tokens | text
Output: text | Function callingTool choice | 131.1K | Same provider Overall 91% |
| Qwen3-235B-A22B-Instruct-2507 deepinfra | In $0.0900 / 1M tokens Out $0.6000 / 1M tokens | text
Output: text | Function callingTool choice | 262.1K | Same provider Overall 86% |
| Qwen3-14B deepinfra | In $0.0600 / 1M tokens Out $0.2400 / 1M tokens | text
Output: text | Function callingTool choice | 41.0K | Same provider Overall 83% |
| Qwen2.5-72B-Instruct deepinfra | In $0.1200 / 1M tokens Out $0.3900 / 1M tokens | text
Output: text | Function callingTool choice | 32.8K | Same provider Overall 82% |
| Phi-4 azure_ai | In $0.1250 / 1M tokens Out $0.5000 / 1M tokens | text
Output: text | Function callingTool choice | 16.4K | Text covered Overall 80% |
| Llama-3.3-70B-Instruct azure_ai | In $0.7100 / 1M tokens Out $0.7100 / 1M tokens | text
Output: text | Function callingTool choice | 2.0K | Text covered Overall 73% |
| gpt-3.5-turbo Azure | In $0.5000 / 1M tokens Out $1.5000 / 1M tokens | text
Output: text | Function callingTool choice | 4.1K | Text covered Overall 70% |
| gpt-35-turbo Azure | In $0.5000 / 1M tokens Out $1.5000 / 1M tokens | text
Output: text | Function callingTool choice | 4.1K | Text covered Overall 70% |
| gpt-5-nano Azure | In $0.0500 / 1M tokens Out $0.4000 / 1M tokens | text imagepdf
Output: text | Function callingTool choice | 128.0K | Text covered Overall 67% |
| gpt-5-nano-2025-08-07 Azure | In $0.0500 / 1M tokens Out $0.4000 / 1M tokens | text imagepdf
Output: text | Function callingTool choice | 128.0K | Text covered Overall 67% |
| gpt-35-turbo-16k-0613 Azure | In $3.0000 / 1M tokens Out $4.0000 / 1M tokens | text
Output: text | Function callingTool choice | 4.1K | Text covered Overall 67% |
| gpt-5-nano OpenAI | In $0.0500 / 1M tokens Out $0.4000 / 1M tokens | text imagepdf
Output: text | Function callingTool choice | 128.0K | Text covered Overall 66% |
| gpt-4-0613 Azure | In $30.0000 / 1M tokens Out $60.0000 / 1M tokens | text
Output: text | Function callingTool choice | 4.1K | Text covered Overall 66% |
| gemini-2.0-flash-001 deepinfra | In $0.1000 / 1M tokens Out $0.4000 / 1M tokens | text audiocode
Output: text | Function callingTool choice | 1.0M | Same provider Overall 62% |
| qwen3-30b-a3b-fp8 novita | In $0.0900 / 1M tokens Out $0.4500 / 1M tokens | text
Output: text | Low overlap | 20.0K | Text covered Overall 58% |
| gpt-5-nano-2025-08-07 Azure | In $0.0550 / 1M tokens Out $0.4400 / 1M tokens | text pdf
Output: text | Function callingTool choice | 128.0K | Partial I/O overlap Overall 55% Missing text |
| gpt-5-nano-2025-08-07 Azure | In $0.0550 / 1M tokens Out $0.4400 / 1M tokens | text pdf
Output: text | Function callingTool choice | 128.0K | Partial I/O overlap Overall 55% Missing text |
No models match this filter.