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gpt-oss-120b

watsonx · chat model

gpt-oss-120b is listed here as a chat model from watsonx. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.

Input
$0.1500 / 1M tokens
Output
$0.6000 / 1M tokens
Cached input
N/A
Context
8.2K
Compare similar models Open a side-by-side table using this route and the closest match from the current catalog. Estimate workload cost Use token counts, request volume, and cache assumptions to check a realistic monthly bill. Explore benchmark family Review source-backed benchmark rows for the attached base model family. Check data sources See how pricing data is generated and what still needs provider verification.

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
$0.1500 / 1M tokens
Output
$0.6000 / 1M tokens
Embedding
$0.1500 / 1M tokens

Token limits

Context window
8.2K
Max input tokens
8.2K
Max output tokens
8.2K
Max tokens
8.2K

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

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
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gpt-oss-120b
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In $0.1500 / 1M tokens
Out $0.6000 / 1M tokens
Output: unknown
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Current model
Reference row

Overall blends cost, modality overlap, capabilities, and context.

Model Cost Input shape Features Context Why it is close
gemini-2.0-flash-001
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Out $0.6000 / 1M tokens
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In $0.1500 / 1M tokens
Out $0.6000 / 1M tokens
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gemini-2.0-flash
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In $0.1500 / 1M tokens
Out $0.6000 / 1M tokens
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Out $0.5500 / 1M tokens
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Out $0.5600 / 1M tokens
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Out $0.6000 / 1M tokens
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Out $0.6000 / 1M tokens
Output: unknown
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granite-13b-chat-v2
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Out $0.6000 / 1M tokens
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granite-13b-instruct-v2
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In $0.6000 / 1M tokens
Out $0.6000 / 1M tokens
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Overall 28%
gpt-4o-mini
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In $0.1500 / 1M tokens
Out $0.6000 / 1M tokens
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Phi-3-small-128k-instruct
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In $0.1500 / 1M tokens
Out $0.6000 / 1M tokens
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Phi-3-small-8k-instruct
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Out $0.6000 / 1M tokens
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command-r
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In $0.1500 / 1M tokens
Out $0.6000 / 1M tokens
Output: unknown
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command-r-08-2024
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In $0.1500 / 1M tokens
Out $0.6000 / 1M tokens
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In $0.2000 / 1M tokens
Out $0.2000 / 1M tokens
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Out $0.2000 / 1M tokens
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Out $0.1000 / 1M tokens
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gpt-oss-120b
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In $0.1500 / 1M tokens
Out $0.6000 / 1M tokens
text
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ai21.jamba-instruct-v1:0
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In $0.5000 / 1M tokens
Out $0.7000 / 1M tokens
text
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Low overlap
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Partial I/O overlap
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us.writer.palmyra-x4-v1:0
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In $2.5000 / 1M tokens
Out $10.0000 / 1M tokens
pdftext
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Low overlap
8.2K
Partial I/O overlap
Overall 16%
ai21.j2-mid-v1
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In $12.5000 / 1M tokens
Out $12.5000 / 1M tokens
text
Output: text
Low overlap
8.2K
Partial I/O overlap
Overall 16%
ai21.j2-ultra-v1
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In $18.8000 / 1M tokens
Out $18.8000 / 1M tokens
text
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Partial I/O overlap
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ai21.jamba-1-5-mini-v1:0
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Out $0.4000 / 1M tokens
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ai21.jamba-1-5-large-v1:0
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In $2.0000 / 1M tokens
Out $8.0000 / 1M tokens
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Low overlap
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