// ranked · September 2026

Cheapest LLMs with Tool Calling

Every paid model that supports tool (function) calling, ranked by blended list price — 3:1 input:output per 1M tokens. Free tiers are on their own page.

OpenRouter + LiveBenchAll rankingsAll models

Mistral Nemo is the cheapest paid model with tool calling, at $0.022 per 1M tokens blended. Ling 3.0 Flash follows at $0.032.

Mistral Nemo vs Ling 3.0 Flash, head to head

Top 10

#ModelBlended / 1MContextLiveBenchCapabilities
1Mistral Nemo

mistralai/mistral-nemo

$0.022131K
tools
2Ling 3.0 Flash

inclusionai/ling-3.0-flash

$0.032262K
reasoningtools
3gpt-oss-20b

openai/gpt-oss-20b

$0.036131K
reasoningtools
4Qwen3.7 Flash

qwen/qwen3.7-flash

$0.0551M
reasoningtoolsvision
5Llama 3.1 8B Instruct

meta-llama/llama-3.1-8b-instruct

$0.057131K
tools
6DeepSeek V4 Flash 0423

deepseek/deepseek-v4-flash

$0.0611.0M65.5
reasoningtools
7Nova Micro 1.0

amazon/nova-micro-v1

$0.061128K
tools
8Mercury 2.5

inception/mercury-2.5

$0.068260K
reasoningtools
9Laguna XS 2.1

poolside/laguna-xs-2.1

$0.075262K
reasoningtools
10Gemma 3 12B

google/gemma-3-12b-it

$0.075131K
toolsvision

264 more models qualify — see the full leaderboard.

FAQ

What is the cheapest LLM with tool calling in September 2026?

Mistral Nemo is the cheapest paid model with tool calling, at $0.022 per 1M tokens blended. Ling 3.0 Flash follows at $0.032.

How is this ranking produced?

Every paid model that supports tool (function) calling, ranked by blended list price — 3:1 input:output per 1M tokens. Free tiers are on their own page.

Other rankings

How this ranking is produced

  • One metric, stated above — nothing here is weighted or scored by us. Scores come from LiveBench release 2026-06-25; models without a published run don't appear in score-based rankings.
  • Price, context and capabilities — live from OpenRouter, refreshed every 15 minutes.
  • Ties — scores less than a point apart are called a tie; effort settings alone move a LiveBench score by more than that.

A public benchmark is someone else's workload. Before committing, see LLM & agent evaluation.