Passer au contenu principal

gpt-oss-20b (High)

OpenAIOpen WeightApache 2.0 · Usage Commercial

Description

The gpt-oss-20b model (technically 20.9B parameters) achieves near-parity with OpenAI o4-mini on core reasoning benchmarks, while running efficiently on a single 80 GB GPU. The gpt-oss-20b model delivers similar results to OpenAI o3‑mini on common benchmarks and can run on edge devices with just 16 GB of memory, making it ideal for on-device use cases, local inference, or rapid iteration without costly infrastructure. Both models also perform strongly on tool use, few-shot function calling, CoT reasoning (as seen in results on the Tau-Bench agentic evaluation suite) and HealthBench (even outperforming proprietary models like OpenAI o1 and GPT‑4o). Note: While referred to as '20b' for simplicity, it technically has 20.9B parameters.

Date de sortie
2025-08-05
Paramètres
20.9B
Longueur du contexte
131K
Modalités
text

Radar de capacités

29
general
42
coding
86
reasoning
47
science
50
agents
0
multimodal

Classements

Domaine#RangScoreSource
Classement codage376
38.0
AA
Classement général254
48.0
AA
Science308
46.0
AA

Scores de benchmarks (LLM Stats)

(LLM Stats (zeroeval))

Chat

TAU-bench Retail54.8%Aut.

General

MMLU85.3%Aut.

Healthcare

HealthBench42.5%Aut.
HealthBench Hard10.8%Aut.

Math

AIME 202598.7%Aut.
CodeForces0.74 / 3000Aut.

Reasoning

GPQANYU + Cohere + Anthropic (2023)74.2%Aut.
Humanity's Last Exam10.9%Aut.

Indices d'évaluation AA

(Artificial Analysis)
Aime 25(MAA (Mathematical Association of America))
89.3
Math Index(Artificial Analysis)
89.3
Livecodebench(UC Berkeley + MIT + Cornell (2024))
77.7
Mmlu Pro(TIGER-Lab (Univ. of Waterloo, Toronto, CMU, 2024))
74.8
Gpqa(NYU + Cohere + Anthropic (2023))
68.8
Ifbench(Google Research (2023))
65.1
Tau2(Sierra + U Toronto + Vector Institute (2025))
60.2
Scicode(UIUC + Argonne National Lab (2024))
38.9
Lcr(Artificial Analysis)
34.7
Coding Index(Artificial Analysis)
20.7
Terminalbench V2 1
13.9
Hle(Center for AI Safety + Scale AI (2025))
11.0
Terminalbench Hard(Stanford × Laude Institute (2026))
10.6
Intelligence Index(Artificial Analysis)
9.0
Tau Banking
7.0
Terminalbench V4 0
0.0

Scores par catégorie LLM Stats

(LLM Stats (zeroeval))
Language
90
Legal
90
Finance
90
Physics
70
Biology
70
Chemistry
70
Math
60
Reasoning
60
Chat
50
General
50
Healthcare
50
Communication
50
Tool Calling
50
Vision
10

Tarification

Prix d'entrée$0.07 / 1M tokens
Prix de sortie$0.18 / 1M tokens
Prix mixte (3:1)$0.098 / 1M tokens
Prix de lecture cache$0.009 / 1M tokens

Vitesse

Tokens/sec174.4
Délai du premier token0.43s
Temps de réponse11.90s

Classement des Prix par Fournisseur

Classement des Prix par Fournisseur

26 fournisseurs

Moins cher: DeepInfraPlus cher: Regolo AI
FournisseurEntréeSortie
1DeepInfraMoins cher
$0
$0
2OpenRouter
$0.018
$0.09
3Kilo Gateway
$0.018
$0.09
4IO.NET
$0.03
$0.14
5CoreWeave
$0.03
$0.13
6Deep Infra
$0.03
$0.14
7Vercel AI Gateway
$0.03
$0.14
8NovitaAI
$0.04
$0.15
9SiliconFlow
$0.04
$0.18
10DevPass (LLM Gateway)
$0.04
$0.19
11Merge Gateway
$0.04
$0.2
12Cortecs
$0.045
$0.167
13Helicone
$0.05
$0.2
14OVHcloud AI Endpoints
$0.05
$0.18
15FastRouter
$0.05
$0.2
16Together AI
$0.05
$0.2
17OpenAIPRINCIPAL
$0.07
$0.18
18FrogBot
$0.07
$0.2
19Neon
$0.07
$0.3
20Pioneer
$0.07
$0.3
21Groq
$0.075
$0.3
22Hugging Face
$0.1
$0.5
23Opper
$0.11622
$0.48812
24STACKIT
$0.18
$0.29
25NanoGPT
$0.2
$0.3
26Regolo AI
$0.4
$1.8

Comparer les prix entre différents fournisseurs API pour ce modèle.

Sources externes