
Best Local & Open-Source LLMs for OpenClaw (2026)
Community-voted rankings for running OpenClaw with local and open-source models
Our Picks
Best Overall Local
Mixtral 8x7B Instruct
Best Small Model
Mistral 7B Instruct v0.2
Best for Coding
Qwen2.5 Coder 7B
Provider | Model | Input $/M | Output $/M | Vote | Score |
|---|---|---|---|---|---|
$0.140 | $0.420 | 40+4 | |||
$0.140 | $0.200 | 10+1 | |||
QW | $0.200 | $0.200 | 000 | ||
$0.200 | $0.200 | 000 | |||
$0.200 | $0.200 | 000 | |||
QW | $0.050 | $0.200 | 000 | ||
$0.000 | $0.000 | 000 | |||
LQ | $0.010 | $0.020 | 000 | ||
LQ | $0.010 | $0.020 | 000 | ||
$0.100 | $0.100 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.100 | $0.200 | 000 | |||
- | $0.000 | $0.000 | 000 | ||
$0.800 | $1.200 | 000 | |||
CO | $0.037 | $0.150 | 000 | ||
$0.150 | $0.150 | 000 | |||
QW | $0.200 | $0.200 | 000 | ||
$0.500 | $0.500 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.100 | $0.100 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.200 | $0.200 | 000 | |||
QW | $0.200 | $0.200 | 000 | ||
QW | $0.100 | $0.100 | 000 | ||
QW | $0.200 | $0.200 | 000 | ||
$0.170 | $0.170 | 000 | |||
$0.200 | $0.200 | 000 | |||
QW | $0.200 | $0.200 | 000 | ||
QW | $0.100 | $0.100 | 000 | ||
QW | $0.200 | $0.200 | 000 | ||
QW | $0.200 | $0.200 | 000 | ||
QW | $0.200 | $0.200 | 000 | ||
QW | $0.200 | $0.200 | 000 | ||
QW | $0.100 | $0.100 | 000 | ||
QW | $0.200 | $0.200 | 000 | ||
QW | $0.200 | $0.200 | 000 | ||
$0.200 | $0.200 | 000 | |||
DS | $0.100 | $0.100 | 000 | ||
DS | $0.200 | $0.200 | 000 | ||
$0.200 | $0.200 | 000 | |||
$0.200 | $0.200 | 000 | |||
AR | $0.045 | $0.150 | 000 | ||
$0.100 | $0.200 | 000 | |||
$0.120 | $0.200 | 000 | |||
DS | $0.200 | $0.200 | 000 | ||
DS | $0.200 | $0.200 | 000 | ||
DS | $0.200 | $0.200 | 000 | ||
$0.100 | $0.100 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.200 | $0.200 | 000 | |||
QW | $0.200 | $0.200 | 000 | ||
QW | $0.100 | $0.100 | 000 | ||
QW | $0.100 | $0.100 | 000 | ||
QW | $0.200 | $0.200 | 000 | ||
$0.150 | $0.150 | 000 | |||
$0.100 | $0.100 | 000 | |||
NV | $0.000 | $0.000 | 000 | ||
NV | $0.000 | $0.000 | 000 | ||
$0.200 | $0.200 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.100 | $0.100 | 000 | |||
$0.100 | $0.100 | 000 | |||
$0.050 | $0.080 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.500 | $0.500 | 000 | |||
$0.170 | $0.170 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.200 | $0.200 | 000 | |||
NV | $0.200 | $0.200 | 000 | ||
Z | $0.600 | $1.800 | 000 | ||
$0.200 | $0.200 | 000 | |||
$0.300 | $0.300 | 000 | |||
DS | $0.200 | $0.200 | 000 | ||
$0.200 | $0.200 | 000 | |||
$0.500 | $0.500 | 000 | |||
$0.070 | $0.070 | 000 | |||
$0.200 | $0.200 | 000 | |||
$0.240 | $0.240 | 000 | |||
$0.200 | $0.200 | 000 | |||
QW | $0.050 | $0.150 | 000 | ||
$0.300 | $0.300 | 000 | |||
QW | $0.030 | $0.090 | 000 | ||
$0.800 | $1.200 | 000 | |||
$0.040 | $0.080 | 000 | |||
$0.040 | $0.130 | 000 | |||
$0.000 | $0.000 | 000 | |||
$0.400 | $0.400 | 000 | |||
$0.100 | $0.100 | 000 | |||
$0.040 | $0.040 | 000 | |||
$0.100 | $0.100 | 000 | |||
IB | $0.000 | $0.000 | 000 | ||
$0.300 | $0.300 | 000 | |||
QW | $0.040 | $0.100 | 000 | ||
$0.060 | $0.060 | 000 | |||
$0.170 | $0.430 | 000 | |||
$0.030 | $0.050 | 000 | |||
$0.020 | $0.020 | 000 | |||
$0.049 | $0.049 | 000 | |||
QW | $0.080 | $0.200 | 000 | ||
QW | $0.100 | $0.100 | 000 | ||
QW | $0.100 | $0.100 | 000 | ||
$0.000 | $0.000 | 000 | |||
$0.150 | $0.150 | 000 | |||
QW | $0.200 | $0.200 | 000 | ||
$0.000 | $0.000 | 000 | |||
S1 | $0.040 | $0.050 | 000 | ||
$0.020 | $0.040 | 000 | |||
$0.140 | $0.140 | 000 | |||
$0.030 | $0.080 | 000 | |||
$0.059 | $0.059 | 000 | |||
$0.140 | $0.200 | 000 | |||
$0.000 | $0.000 | 000 | |||
$0.140 | $0.420 | 000 | |||
$0.030 | $0.040 | 000 | |||
U9 | $0.300 | $0.300 | 000 | ||
GR | $0.060 | $0.060 | 000 | ||
$0.100 | $0.100 | 000 | |||
$0.200 | $0.200 | 000 | |||
QW | $0.200 | $0.200 | 000 | ||
$0.200 | $0.200 | 000 | |||
$0.020 | $0.040 | 01-1 | |||
$0.020 | $0.050 | 01-1 |
Vote for open-source models that work well (or don't) with OpenClaw.
Pricing from OpenRouter.
Running OpenClaw with a Local Model
OpenClaw supports local models via OpenAI-compatible APIs. The easiest way to run a model locally is with Ollama or llama.cpp, both of which expose a local API endpoint that OpenClaw can connect to.
VRAM Requirements
7B models need ~6GB VRAM (4-bit quantized). 13B models need ~10GB. 70B models need ~40GB or multi-GPU. If you're on CPU-only, smaller quantized models (Q4) are usable but slow.
Recommended: Ollama
Install Ollama, run ollama pull llama3.3, then point OpenClaw to http://localhost:11434/v1.
Alternative: llama.cpp server
For more control over quantization and performance, llama.cpp's server mode gives you a full OpenAI-compatible API with fine-grained settings.
About This Leaderboard
This leaderboard shows community votes specifically for open-source and locally-runnable models used with OpenClaw. Models are filtered to include those from open-source providers: Meta (Llama), Mistral, Qwen (Alibaba), Google (Gemma), DeepSeek, Microsoft (Phi), and similar open-weight families.
Running local models with OpenClaw gives you full privacy, zero API costs, and offline capability — at the cost of needing hardware and accepting some quality trade-offs versus frontier API models.