venice-models

venice-models is a skill for Claude Code, Codex from 0xatd/cheaptokens-skills. It costs 66 tokens per session (2,786 once invoked), scanned A, a copy of venice-models, MIT.

A model-discovery guide for the Venice AI service, which lists available models and the abilities, limits, aliases, and prices associated with them.

In plain words
What is it for?
Use it to find models for text, images, video, audio, code, and other tasks; select models by traits such as speed or quality; resolve old model names; and estimate costs.
Why use it?
It helps an application choose a suitable model and reject requests that exceed its limits before sending them.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to find models for text, images, video, audio, code, and other tasks; select models by traits such as speed or quality; resolve old model names; and estimate costs.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/0xatd/cheaptokens-skills/venice-models
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add 0xatd/cheaptokens-skills --skill venice-models
Clone the repo
git clone --depth 1 https://github.com/0xatd/cheaptokens-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for venice-models

README.md
[![agentmods](https://agentmods.dev/badge/skills/0xatd/cheaptokens-skills/venice-models/github.svg)](https://agentmods.dev/skills/0xatd/cheaptokens-skills/venice-models)
Your own site
<a href="https://agentmods.dev/skills/0xatd/cheaptokens-skills/venice-models"><img src="https://agentmods.dev/badge/skills/0xatd/cheaptokens-skills/venice-models/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for venice-models

Your own site · 80×15
<a href="https://agentmods.dev/skills/0xatd/cheaptokens-skills/venice-models"><img src="https://agentmods.dev/badge/skills/0xatd/cheaptokens-skills/venice-models.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,786 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00066 $0.02786
Opus 5 $0.00033 $0.01393
Sonnet 5 $0.00013 $0.00557
Haiku 4.5 $0.00007 $0.00279

Measured 11d ago against content hash 43eb32f2c57b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

venice-models scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl "https://api.venice.ai/api/v1/models?type=text"
Origin

This is a copy

100% identical to venice-models — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/venice-models/SKILL.md · 184 lines

How it starts

The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Venice Models

Three read-only endpoints for model discovery — all GET:

Endpoint Returns
/models Full model catalog with model_spec (capabilities, constraints, pricing).
/models/traits Trait → model ID mapping (e.g. "default", "fastest", "default_reasoning", "highest_quality").
/models/compatibility_mapping Legacy / OpenAI / third-party model ID → Venice model ID aliases.

All three take an optional ?type= filter: text, image, video, music, tts, asr, embedding, upscale, inpaint, all, code.

All three are authenticated (Bearer API key or x402 SIWE) like every other /api/v1 route.

Use when

  • You need to pick a model at runtime based on capabilities (vision, reasoning, function calling, E2EE, X search, multi-image, …).
  • You need to validate a request against a model's constraints (prompt length, aspect ratio, resolution, steps).
  • You need the current price per million tokens / per image / per second / per 1k chars to build a cost estimate.
  • You want to resolve a user-friendly trait name (e.g. default, default_reasoning, highest_quality) or a frontier-style ID (openai-gpt-54-pro, claude-opus-4-7) to a concrete Venice model ID.

GET /models

curl "https://api.venice.ai/api/v1/models?type=text"
{
  "object": "list",
  "type": "text",
  "data": [
    {
      "id": "zai-org-glm-5-1",
      "created": 1699000000,
      "model_spec": {
        "name": "GLM 5.1",
        "description": "Balanced blend of speed and capability...",
        "availableContextTokens": 200000,
        "maxCompletionTokens": 24000,
        "privacy": "private",
        "beta": false,
        "betaModel": false,
        "modelSource": "https://huggingface.co/zai-org/GLM-5.1",
        "offline": false,
        "capabilities": { ... },
        "constraints": { ... },
        "pricing": { ... },
        "regionRestrictions": ["US"],
        "deprecation": {"date": "2025-03-01T00:00:00.000Z"}
      }
    }
  ]
}

Read the full file on GitHub · 184 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 184 lines · 66 tokens per session scan A 43eb32f2c57b

Subscribe to this mod's changes

venice-models is a skill published in the GitHub repository 0xatd/cheaptokens-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 66 tokens to every session and 2,786 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to venice-models, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

together-ai-inference

Serverless inference, fine-tuning, embeddings, image generation, and batch processing on 200+ open-source models via an OpenAI-compatible API. Use when you need fast, cost-effective access to open-source LLMs without managing infrastructure.

synthetic-sciences/openscience · 55 tokens

groq-inference

Ultra-fast LLM inference on custom LPU hardware. OpenAI-compatible API at api.groq.com. Lowest latency in the industry (500-1000+ tok/s). Supports chat completions, vision, audio (Whisper STT + TTS), tool calling, JSON mode, and streaming. Free tier available. Inference only — no training.

synthetic-sciences/openscience · 77 tokens

blockrun

Pay-per-call access to AI models, real-time data, media generation and multi-chain RPC over x402 micropayments (USDC on Base or Solana). No API keys, no accounts, no subscriptions. Start here when you have the BlockRun MCP installed and need to know WHICH tool answers a question, how the wallet works, or how to make a…

BlockRunAI/blockrun-mcp · 241 tokens

fireworks-ai-inference

Fast inference and fine-tuning platform with serverless and on-demand GPU deployments. OpenAI-compatible API for chat completions, embeddings, function calling, vision, and structured output. Supports SFT, DPO, and RL fine-tuning. SOC2 + HIPAA compliant.

synthetic-sciences/openscience · 62 tokens

graphify

Converts this codebase into a queryable knowledge graph so AI sessions query graph.json (71.5x fewer tokens) instead of reading raw source files. Integrates with Claude Code and Codex via repo hooks that auto-refresh on session start and after turns.

strikersam/autonomous-ai-agency · 56 tokens

data-quality-audit

Audit training data and tokenizer pipelines for quality issues that silently degrade LLM training. Data problems are the #1 underdiagnosed cause of poor model performance — most tutorials skip this entirely.

strikersam/autonomous-ai-agency · 0 tokens