Compatible models for BrainOutput Office Appliance (RTX 3060 12GB)
Open models graded for the BrainOutput Office Appliance (RTX 3060 12GB) (top config: 32GB, ~12GB AI memory), best fit first. Lower configurations run fewer of these.
- CodeLlama 13BCodeLlama · ~13B · 16K ctx · Llama Community License
Fits at Q4_K_M (~8GB) with ~2.6GB headroom — about 1 concurrent instance.
Q4_K_M · ~8GBRuns well - Gemma 3 12BGemma 3 · ~12B · 128K ctx · Gemma Terms of Use
Fits at Q4_K_M (~8GB) with ~2.6GB headroom — about 1 concurrent instance.
Q4_K_M · ~8GBRuns well - Mistral Nemo 12BMistral · ~12B · 128K ctx · Apache-2.0
Fits at Q4_K_M (~8GB) with ~2.6GB headroom — about 1 concurrent instance.
Q4_K_M · ~8GBRuns well - Gemma 2 9BGemma · ~9B · 8K ctx · Gemma Terms of Use
Fits at Q8_0 (~10GB) with ~0.6GB headroom — about 1 concurrent instance.
Q8_0 · ~10GBRuns well - Llama 3.1 8BLlama · ~8B · 128K ctx · Llama Community License
Fits at Q8_0 (~9GB) with ~1.6GB headroom — about 1 concurrent instance.
Q8_0 · ~9GBRuns well - Qwen3 8BQwen · ~8B · 128K ctx · Apache-2.0
Fits at Q8_0 (~9GB) with ~1.6GB headroom — about 1 concurrent instance.
Q8_0 · ~9GBRuns well - Granite 3 8BGranite · ~8B · 128K ctx · Apache-2.0
Fits at Q8_0 (~9GB) with ~1.6GB headroom — about 1 concurrent instance.
Q8_0 · ~9GBRuns well - DeepSeek-R1 Distill 8BDeepSeek · ~8B · 128K ctx · MIT
Fits at Q8_0 (~9GB) with ~1.6GB headroom — about 1 concurrent instance.
Q8_0 · ~9GBRuns well - Qwen2.5 7B InstructQwen2.5 · ~7.6B · 33K ctx · apache-2.0
Fits at Q8_0 (~8.4GB) with ~2.2GB headroom — about 1 concurrent instance.
Q8_0 · ~8.4GBRuns well - Qwen2.5 Coder 7B InstructQwen2.5 · ~7.6B · 131K ctx · apache-2.0
Fits at Q8_0 (~8.4GB) with ~2.2GB headroom — about 1 concurrent instance.
Q8_0 · ~8.4GBRuns well - Qwen2.5 7BQwen · ~7B · 128K ctx · Apache-2.0
Fits at Q8_0 (~8GB) with ~2.6GB headroom — about 1 concurrent instance.
Q8_0 · ~8GBRuns well - Mistral 7BMistral · ~7B · 32K ctx · Apache-2.0
Fits at Q8_0 (~8GB) with ~2.6GB headroom — about 1 concurrent instance.
Q8_0 · ~8GBRuns well - Qwen2.5-Coder 7BQwen · ~7B · 128K ctx · Apache-2.0
Fits at Q8_0 (~8GB) with ~2.6GB headroom — about 1 concurrent instance.
Q8_0 · ~8GBRuns well - CodeLlama 7BCodeLlama · ~7B · 16K ctx · Llama Community License
Fits at Q8_0 (~8GB) with ~2.6GB headroom — about 1 concurrent instance.
Q8_0 · ~8GBRuns well - StarCoder2 7BStarCoder · ~7B · 16K ctx · BigCode OpenRAIL-M
Fits at Q8_0 (~8GB) with ~2.6GB headroom — about 1 concurrent instance.
Q8_0 · ~8GBRuns well - Gemma 3 4BGemma 3 · ~4B · 128K ctx · Gemma Terms of Use
Fits at FP16 (~8GB) with ~2.6GB headroom — about 1 concurrent instance.
FP16 · ~8GBRuns well - Phi-3.5 Mini (3.8B)Phi · ~3.8B · 128K ctx · MIT
Fits at FP16 (~8GB) with ~2.6GB headroom — about 1 concurrent instance.
FP16 · ~8GBRuns well - Llama 3.2 3BLlama · ~3B · 128K ctx · Llama Community License
Fits at FP16 (~7GB) with ~3.6GB headroom — about 1 concurrent instance.
FP16 · ~7GBRuns well - Qwen2.5 3BQwen · ~3B · 32K ctx · Qwen Research License
Fits at FP16 (~6GB) with ~4.6GB headroom — about 1 concurrent instance.
FP16 · ~6GBRuns well - StarCoder2 3BStarCoder · ~3B · 16K ctx · BigCode OpenRAIL-M
Fits at FP16 (~6GB) with ~4.6GB headroom — about 1 concurrent instance.
FP16 · ~6GBRuns well - Gemma 2 2BGemma · ~2B · 8K ctx · Gemma Terms of Use
Fits at FP16 (~4GB) with ~6.6GB headroom — about 2 concurrent instances.
FP16 · ~4GBRuns well - Granite 3 2BGranite · ~2B · 128K ctx · Apache-2.0
Fits at FP16 (~4GB) with ~6.6GB headroom — about 2 concurrent instances.
FP16 · ~4GBRuns well - SmolLM2 1.7BSmolLM · ~1.7B · 8K ctx · Apache-2.0
Fits at FP16 (~3.4GB) with ~7.2GB headroom — about 3 concurrent instances.
FP16 · ~3.4GBRuns well - Qwen2.5 1.5BQwen · ~1.5B · 32K ctx · Apache-2.0
Fits at FP16 (~3GB) with ~7.6GB headroom — about 3 concurrent instances.
FP16 · ~3GBRuns well - DeepSeek-R1 Distill 1.5BDeepSeek · ~1.5B · 128K ctx · MIT
Fits at FP16 (~4GB) with ~6.6GB headroom — about 2 concurrent instances.
FP16 · ~4GBRuns well - Qwen2.5-Coder 1.5BQwen · ~1.5B · 32K ctx · Apache-2.0
Fits at FP16 (~3GB) with ~7.6GB headroom — about 3 concurrent instances.
FP16 · ~3GBRuns well - Llama 3.2 1BLlama · ~1B · 128K ctx · Llama Community License
Fits at FP16 (~3GB) with ~7.6GB headroom — about 3 concurrent instances.
FP16 · ~3GBRuns well - Qwen2.5 0.5BQwen · 32K ctx · Apache-2.0
Fits at FP16 (~1GB) with ~9.6GB headroom — about 10 concurrent instances.
FP16 · ~1GBRuns well - StarCoder2 15BStarCoder · ~15B · 16K ctx · BigCode OpenRAIL-M
Fits at Q4_K_M (~10GB) but limited bandwidth makes token generation slow for a 15B model.
Q4_K_M · ~10GBRuns slowly - Qwen2.5 14BQwen · ~14B · 128K ctx · Apache-2.0
Fits at Q4_K_M (~10GB) but limited bandwidth makes token generation slow for a 14B model.
Q4_K_M · ~10GBRuns slowly - Qwen3 14BQwen · ~14B · 128K ctx · Apache-2.0
Fits at Q4_K_M (~10GB) but limited bandwidth makes token generation slow for a 14B model.
Q4_K_M · ~10GBRuns slowly - Phi-3 Medium (14B)Phi · ~14B · 128K ctx · MIT
Fits at Q4_K_M (~9GB) but limited bandwidth makes token generation slow for a 14B model.
Q4_K_M · ~9GBRuns slowly - Phi-4 (14B)Phi · ~14B · 16K ctx · MIT
Fits at Q4_K_M (~9GB) but limited bandwidth makes token generation slow for a 14B model.
Q4_K_M · ~9GBRuns slowly - DeepSeek-R1 Distill 14BDeepSeek · ~14B · 128K ctx · MIT
Fits at Q4_K_M (~10GB) but limited bandwidth makes token generation slow for a 14B model.
Q4_K_M · ~10GBRuns slowly - Qwen2.5-Coder 14BQwen · ~14B · 128K ctx · Apache-2.0
Fits at Q4_K_M (~10GB) but limited bandwidth makes token generation slow for a 14B model.
Q4_K_M · ~10GBRuns slowly - DeepSeek-R1 671B (MoE)DeepSeek · ~671B · 128K ctx · MIT
Even the smallest quantization (~400GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - Llama 3.1 405BLlama · ~405B · 128K ctx · Llama Community License
Even the smallest quantization (~230GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - Qwen3 235B-A22B (MoE)Qwen · ~235B · 128K ctx · Apache-2.0
Even the smallest quantization (~130GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - Qwen2.5 72BQwen · ~72B · 128K ctx · Qwen License
Even the smallest quantization (~44GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - Llama 3.1 70BLlama · ~70B · 128K ctx · Llama Community License
Even the smallest quantization (~42GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - Llama 3.3 70BLlama · ~70B · 128K ctx · Llama Community License
Even the smallest quantization (~42GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - DeepSeek-R1 Distill Llama 70BDeepSeek · ~70B · 128K ctx · MIT
Even the smallest quantization (~42GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - Mixtral 8x7B (MoE)Mistral · ~47B · 32K ctx · Apache-2.0
Even the smallest quantization (~28GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - CodeLlama 34BCodeLlama · ~34B · 16K ctx · Llama Community License
Even the smallest quantization (~21GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - Qwen2.5 32BQwen · ~32B · 128K ctx · Apache-2.0
Even the smallest quantization (~20GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - Qwen3 32BQwen · ~32B · 128K ctx · Apache-2.0
Even the smallest quantization (~20GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - DeepSeek-R1 Distill 32BDeepSeek · ~32B · 128K ctx · MIT
Even the smallest quantization (~20GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - Qwen2.5-Coder 32BQwen · ~32B · 128K ctx · Apache-2.0
Even the smallest quantization (~20GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - Gemma 2 27BGemma · ~27B · 8K ctx · Gemma Terms of Use
Even the smallest quantization (~17GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - Gemma 3 27BGemma 3 · ~27B · 128K ctx · Gemma Terms of Use
Even the smallest quantization (~17GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - Mistral Small 24BMistral · ~24B · 32K ctx · Apache-2.0
Even the smallest quantization (~14GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended - DeepSeek-Coder V2 (class)DeepSeek · ~16B · 128K ctx · DeepSeek License
Even the smallest quantization (~11GB) exceeds usable memory (~10.6GB). Choose a smaller model or step up the hardware.
Not recommended
All BrainOutput Office Appliance (RTX 3060 12GB) configurations →
Run these models on the BrainOutput Office Appliance (RTX 3060 12GB)
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