modelparams.dev
API GitHub

Providers

Alibaba Anthropic Cohere DeepSeek Google Meta MiniMax Mistral Moonshot AI Nvidia OpenAI Perplexity xAI Xiaomi Z.ai

Providers

Alibaba Anthropic Cohere DeepSeek Google Meta MiniMax Mistral Moonshot AI Nvidia OpenAI Perplexity xAI Xiaomi Z.ai
Sampling number 32 models

Frequency penalty frequency_penalty

Penalizes words based on how often they already appear in the generated text.

Type
number
Default
0
Range
-2 – 2

frequency_penalty by model

The exact type, default, range, and conditions for frequency_penalty on each model that documents it.

Model Provider Type Default Range / values Condition
Command A 03 2025 Cohere number 0 0…1 step 0.1 —
Command A Plus 05 2026 Cohere number 0 0…1 step 0.1 —
Command A Reasoning 08 2025 Cohere number 0 0…1 step 0.1 —
Command A Translate 08 2025 Cohere number 0 0…1 step 0.1 —
Command A Vision 07 2025 Cohere number 0 0…1 step 0.1 —
Command R 08 2024 Cohere number 0 0…1 step 0.1 —
Command R Plus 08 2024 Cohere number 0 0…1 step 0.1 —
Command R7b 12 2024 Cohere number 0 0…1 step 0.1 —
Codestral Latest Mistral number 0 -2…2 step 0.1 —
Devstral 2512 Mistral number 0 -2…2 step 0.1 —
Devstral Latest Mistral number 0 -2…2 step 0.1 —
Magistral Medium Latest Mistral number 0 -2…2 step 0.1 —
Magistral Small Latest Mistral number 0 -2…2 step 0.1 —
Ministral 14b Latest Mistral number 0 -2…2 step 0.1 —
Ministral 3b Latest Mistral number 0 -2…2 step 0.1 —
Ministral 8b Latest Mistral number 0 -2…2 step 0.1 —
Mistral Large Latest Mistral number 0 -2…2 step 0.1 —
Mistral Medium 3.5 Mistral number 0 -2…2 step 0.1 —
Mistral Medium Latest Mistral number 0 -2…2 step 0.1 —
Mistral Small Latest Mistral number 0 -2…2 step 0.1 —
Open Mistral Nemo Mistral number 0 -2…2 step 0.1 —
Moonshot v1 128K Moonshot AI number 0 -2…2 step 0.1 —
Moonshot v1 32K Moonshot AI number 0 -2…2 step 0.1 —
Moonshot v1 8K Moonshot AI number 0 -2…2 step 0.1 —
Llama 3.1 Nemoguard 8b Topic Control Nvidia number 0 -2…2 —
Llama 3.1 Nemotron Nano 8b V1 Nvidia number 0 -2…2 —
Llama 3.1 Nemotron Ultra 253b V1 Nvidia number 0 -2…2 —
Llama 3.3 Nemotron Super 49b V1 Nvidia number 0 -2…2 —
Llama 3.3 Nemotron Super 49b V1.5 Nvidia number 0 -2…2 —
Nemotron Mini 4b Instruct Nvidia number 0 -2…2 —
Riva Translate 4b Instruct V1.1 Nvidia number 0 -2…2 —
Mimo V2.5 Pro Xiaomi number 0 -2…2 step 0.1 —

Models without frequency_penalty documented yet

These models don't list frequency_penalty in the catalog. That may mean the provider doesn't accept it, or it simply hasn't been added yet — the data is community-maintained.

Alibaba

Qwen Flash Qwen Plus Qwen3 Coder Flash Qwen3 Coder Plus Qwen3 Max Qwen3.5 Qwen3.5 Flash Qwq Plus

Anthropic

Claude 3 Opus 20240229 Claude 3 Opus Latest Claude 3.5 Haiku 20241022 Claude 3.5 Haiku Latest Claude 3.5 Sonnet 20241022 Claude 3.5 Sonnet Latest Claude 3.7 Sonnet 20250219 Claude 3.7 Sonnet Latest Claude Fable 5 Claude Fable 5 Claude Haiku 4 Claude Haiku 4 Claude Haiku 4.5 Claude Haiku 4.5 Claude Haiku 4.5 20251001 Claude Haiku 4.5 20251001 Claude Opus 4 Claude Opus 4 20250514 Claude Opus 4 20250514 Claude Opus 4.1 20250805 Claude Opus 4.1 20250805 Claude Opus 4.5 20251101 Claude Opus 4.5 20251101 Claude Opus 4.6 Claude Opus 4.6 Claude Opus 4.7 Claude Opus 4.7 Claude Opus 4.8 Claude Opus 4.8 Claude Sonnet 4 Claude Sonnet 4 20250514 Claude Sonnet 4 20250514 Claude Sonnet 4.5 Claude Sonnet 4.5 Claude Sonnet 4.5 20250929 Claude Sonnet 4.5 20250929 Claude Sonnet 4.6 Claude Sonnet 4.6

DeepSeek

Deepseek Chat Deepseek Reasoner Deepseek V4 Flash Deepseek V4 Pro

Google

Gemini 2.5 Flash Gemini 2.5 Flash Gemini 2.5 Flash Lite Gemini 2.5 Flash Lite Gemini 2.5 Pro Gemini 2.5 Pro Gemini 3 Flash Preview Gemini 3.1 Flash Lite Gemini 3.1 Flash Lite Preview Gemini 3.1 Pro Preview Gemini 3.5 Flash

Meta

Llama 3.3 70B Instruct Llama 3.3 8B Instruct Llama 4 Maverick 17B 128E Instruct FP8 Llama 4 Scout 17B 16E Instruct FP8

MiniMax

MiniMax M2 MiniMax M2 MiniMax M2.1 MiniMax M2.1 MiniMax M2.1 Highspeed MiniMax M2.1 Highspeed MiniMax M2.5 MiniMax M2.5 MiniMax M2.5 Highspeed MiniMax M2.5 Highspeed MiniMax M2.7 MiniMax M2.7 MiniMax M2.7 Highspeed MiniMax M2.7 Highspeed Minimax M3 MiniMax M3

Moonshot AI

Kimi K2.5 Kimi K2.6 Kimi K2.6 Kimi K2.7 Code Kimi K2.7 Code Highspeed

Nvidia

Gliner Pii Llama 3.1 Nemotron Safety Guard 8b V3 Nemoguard Jailbreak Detect Nemotron 3 Nano 30b A3b Nemotron 3 Super 120b A12b Nemotron 3 Ultra Nemotron 3 Ultra 550b A55b Nemotron Content Safety Reasoning 4b Usdcode Llama 3.1 70b Instruct

OpenAI

Chatgpt 4o Latest Gpt 3.5 Turbo Gpt 4 Turbo Gpt 4 Turbo 2024-04-09 Gpt 4.1 Gpt 4.1 Mini Gpt 4.1 Nano Gpt 4o 2024-11-20 Gpt 5 Gpt 5 Chat Latest Gpt 5 Mini Gpt 5 Nano Gpt 5.1 Gpt 5.1 Codex Gpt 5.1 Codex Max Gpt 5.2 Gpt 5.2 Gpt 5.2 Codex Gpt 5.3 Codex Gpt 5.3 Codex Gpt 5.3 Codex Spark Gpt 5.4 Gpt 5.4 Gpt 5.4 Mini Gpt 5.4 Mini Gpt 5.4 Nano Gpt 5.4 Pro Gpt 5.4 Pro Gpt 5.5 Gpt 5.5 Gpt 5.5 Pro Gpt 5.5 Pro GPT-4o GPT-4o mini o1 O1 Preview o1-mini o3 O3 Pro o3-mini o4-mini

Perplexity

Sonar Sonar Deep Research Sonar Pro Sonar Reasoning Pro

xAI

Grok 4.20 0309 Non Reasoning Grok 4.20 0309 Reasoning Grok 4.20 Multi Agent 0309 Grok 4.3 Grok Build 0.1

Xiaomi

Mimo V2.5 Mimo V2.5

Z.ai

GLM-4.5 GLM-4.5 GLM-4.5-Air GLM-4.5-Air GLM-4.5-AirX GLM-4.5-Flash GLM-4.5-X GLM-4.6 GLM-4.6 GLM-4.7 GLM-4.7 GLM-4.7-Flash GLM-4.7-FlashX GLM-5 GLM-5 GLM-5-Turbo GLM-5-Turbo GLM-5.1 GLM-5.1

Related sampling parameters

Temperature temperature Top P top_p Top K top_k Presence penalty presence_penalty Seed seed Do sample do_sample Random seed random_seed Seed generationConfig.seed Temperature generationConfig.temperature Top K generationConfig.topK Top P generationConfig.topP Top K extra_body.top_k

Resources

All parameters Use the API Full catalog

How to use

Building with an AI agent? Hit Copy to grab this whole guide as Markdown and paste it in — or point your agent straight at /llms.txt.

modelparams.dev is an open, community-maintained catalog of model parameters. Each entry shows the knobs you can turn — type, default, range, and the conditions that gate it.

The same model accessed via an API key and via a subscription usually exposes a different set of parameters. We list both as separate entries so the data stays honest.

Catalog API

The full catalog is static JSON, CORS-enabled, served from the edge.

curl https://modelparams.dev/api/v1/models.json

Each entry is keyed by provider/model for API-key variants; subscription variants append -subscription.

If you only need the params for one model contract, use the providerless endpoint. Subscription contracts are model slugs with -subscription. 

curl https://modelparams.dev/api/v1/params/gpt-5.5.json
curl https://modelparams.dev/api/v1/params/gpt-5.5-subscription.json

Single model

curl https://modelparams.dev/api/v1/models/anthropic/claude-opus-4-7.json
curl https://modelparams.dev/api/v1/models/anthropic/claude-opus-4-7-subscription.json

JSON Schema

Every entry validates against a JSON Schema you can use in your editor or pipeline. 

curl https://modelparams.dev/api/v1/schema.json

Add this header to any YAML you author for autocomplete in VS Code: 

# yaml-language-server: $schema=https://modelparams.dev/api/v1/schema.json

Logos

Provider logos are available at /assets/logos/{provider}.svg where {provider} is the provider slug. They use currentColor so they inherit your text color. 

curl https://modelparams.dev/assets/logos/anthropic.svg

Logos are sourced from the models.dev repo (MIT) and used under nominative fair use.

Contribute

The data lives in YAML under models/{provider}/{model}-{auth}.yaml in the GitHub repo. Open a PR; CI validates against the schema and rebuilds.

Edit on GitHub MIT licensed