Your rig

Radeon RX 6700 XT · 12 GB

64 GB system RAM · RDNA 2 · 384 GB/s · 10.6 GB usable VRAM
Edit hardware Export as JSON

Context length

KV cache at f16, 128K tokens

Quality floor
Q8_0 — near-lossless Q6_K Q5_K_M Q4_K_M — recommended Q3_K_M Q2_K — damaged
KV cache type
System RAM (GB)
Runtime
Ollamallama.cppLM StudiovLLM

4 of 5 runtimes drive this device.

Allow CPU offload Include partial-offload fits

Offloaded layers run at 60 GB/s host bandwidth — expect single-digit tokens per second.

Which one should I actually run?

Best models for your Radeon RX 6700 XT

Updated 21 Aug 2026 5 new this week, 14 this month

What do you want to do? Each row is the best-ranked model on that use case's shortlist that fits at Q6_K and 128K. The ordering is editorial; the sizes and speeds are computed. How the shortlists work.

RecommendationModelWhyQuant · totalTok/s est.
Best overall Gemma 4 E4B
Google · Apache 2.0
Laptop class with images and audio in. Q6_K · 8.5 GB 38 Runs great
Best for coding Qwen3.5 4B
Alibaba · Apache 2.0
A coding agent in 3.4 GB — the 6–8 GB answer. Q6_K · 8.2 GB 65 Runs great
Best reasoning Qwen3.5 4B
Alibaba · Apache 2.0
Step-by-step reasoning in 8 GB. Q6_K · 8.2 GB 65 Runs great
Best for writing Gemma 4 E4B
Google · Apache 2.0
Readable prose on a laptop. Q6_K · 8.5 GB 38 Runs great
Best vision Gemma 4 E4B
Google · Apache 2.0
Laptop vision, audio too. Q6_K · 8.5 GB 38 Runs great
Best for agents Qwen3.5 4B
Alibaba · Apache 2.0
Function calling in 8 GB. Q6_K · 8.2 GB 65 Runs great
Best translation Gemma 4 E4B
Google · Apache 2.0
140+ languages on a laptop. Q6_K · 8.5 GB 38 Runs great
Fastest good model LFM2.5 8B-A1B
Liquid AI · LFM Open License v1.0
1.5B active; designed for laptops without a GPU. Q6_K · 8.5 GB 78 Runs great
Best long context Qwen3.5 4B
Alibaba · Apache 2.0
262K on 8 GB. Q6_K · 8.2 GB
at 128K context
65 Runs great

Everything that fits

Runs great

14 of 76 · fits with headroom for a longer prompt
ModelParamsQuantWeights +KV 128KTotal VRAM headroom Tok/sRuntime
LFM2.5 8B-A1B 8.47B MoE / 1.5B act Q6_K 6.5 GB 1.46 GB 8.5 GB
2.1 GB free
78 Ollama Run
Gemma 4 E4B 8.0B Q6_K 6.1 GB 1.78 GB 8.5 GB
2.1 GB free
38 Ollama Run
Ling 3.0 Tiny 7.9B-A1.3B New 7.9B MoE / 1.3B act Q6_K 6.0 GB 0.84 GB 7.5 GB
3.1 GB free
90 llama.cpp Run
Gemma 4 E2B 5.1B Q6_K 3.9 GB 0.89 GB 5.4 GB
5.2 GB free
60 Ollama Run
Qwen3.5 4B 4.66B Q6_K 3.6 GB 4.00 GB 8.2 GB
2.4 GB free
65 Ollama Run
Gemma 3 4B 4.3B Q6_K 3.3 GB 3.11 GB 7.0 GB
3.6 GB free
71 Ollama Run
Qwen3 4B 4.02B Q6_K 3.1 GB 4.50 GB 8.2 GB
2.4 GB free
76 Ollama Run
LFM2.5 2.6B New 2.7B Q6_K 2.1 GB 2.00 GB 4.7 GB
5.9 GB free
113 llama.cpp Run
Qwen3.5 2B 2.27B Q6_K 1.7 GB 1.50 GB 3.8 GB
6.8 GB free
134 Ollama Run
Qwen3 1.7B 1.72B Q6_K 1.3 GB 3.50 GB 5.4 GB
5.2 GB free
177 Ollama Run
Llama 3.2 1B Instruct 1.24B Q6_K 0.9 GB 4.00 GB 5.5 GB
5.1 GB free
245 Ollama Run
Gemma 3 1B 1.0B Q6_K 0.8 GB 0.14 GB 1.5 GB
9.1 GB free
304 Ollama Run
Qwen3.5 0.8B 0.87B Q6_K 0.7 GB 1.50 GB 2.8 GB
7.8 GB free
350 Ollama Run
Qwen3 0.6B 0.6B Q6_K 0.5 GB 3.50 GB 4.6 GB
6.0 GB free
507 Ollama Run

Runs — tight

1 model · fits at 128K, drop context or quant to go longer
ModelParamsQuantWeights +KV 128KTotal VRAM headroom Tok/sRuntime
Mistral 7B Instruct v0.3 7.25B Q6_K 5.5 GB 4.00 GB 10.1 GB
0.5 GB free
42 llama.cpp Run

Won't fit in VRAM

61 models · some are possible with CPU offload
ModelParamsQuantWeights +KV 128KTotal Over budget Tok/sRuntime
Llama 3.3 70B Instruct 70.6B Q6_K 53.9 GB 40.00 GB 94.5 GB +83.9 GB ~0.7 llama.cpp Why
DeepSeek-R1-Distill-Llama 70B 70.6B Q6_K 53.9 GB 40.00 GB 94.5 GB +83.9 GB ~0.7 llama.cpp Why
Qwen3.6 35B-A3B 35.9B MoE / 3.3B act Q6_K 27.4 GB 2.50 GB 30.5 GB +19.9 GB ~7.2 llama.cpp Why
Ornith 1.5 35B-A3B New this week 35.9B MoE / 3.3B act Q6_K 27.4 GB 2.50 GB 30.5 GB +19.9 GB ~7.2 llama.cpp Why
LLM-jp 4 33B Thinking New this week 33.2B Q6_K 25.4 GB 16.00 GB 42.0 GB +31.4 GB ~1.4 llama.cpp Why
Qwen3 32B 32.8B Q6_K 25.0 GB 32.00 GB 57.6 GB +47.0 GB ~1.5 llama.cpp Why
DeepSeek-R1-Distill-Qwen 32B 32.8B Q6_K 25.0 GB 32.00 GB 57.6 GB +47.0 GB ~1.5 llama.cpp Why
Qwen2.5-Coder 32B 32.8B Q6_K 25.0 GB 32.00 GB 57.6 GB +47.0 GB ~1.5 llama.cpp Why
Olmo 3.1 32B Instruct 32.2B Q6_K 24.6 GB 4.75 GB 29.9 GB +19.3 GB ~1.8 llama.cpp Why
Nemotron 3.5 Lightning 30B-A3B New 31.6B MoE / 3.2B act Q6_K 24.1 GB 0.75 GB 25.5 GB +14.9 GB ~8.4 llama.cpp Why
Gemma 4 31B 31.3B Q6_K 23.9 GB 20.78 GB 45.3 GB +34.7 GB ~1.5 llama.cpp Why
GLM-4.7-Flash 30B-A3B 31.2B MoE / 3B act Q6_K 23.8 GB 6.61 GB 31.0 GB +20.4 GB ~6.9 llama.cpp Why
Qwen3 30B-A3B 30.5B MoE / 3.3B act Q6_K 23.3 GB 12.00 GB 35.9 GB +25.3 GB ~5.5 llama.cpp Why
Qwen3 Coder 30B-A3B 30.5B MoE / 3.3B act Q6_K 23.3 GB 12.00 GB 35.9 GB +25.3 GB ~5.5 llama.cpp Why
Muse Glimmer 30B New 29.8B Q6_K 22.8 GB 1.70 GB 25.1 GB +14.5 GB ~2.3 llama.cpp Why
Granite 4.1 30B 28.9B Q6_K 22.1 GB 32.00 GB 54.7 GB +44.1 GB ~1.6 llama.cpp Why
Qwen3.8 27B New this week 27.8B Q6_K 21.2 GB 8.00 GB 29.8 GB +19.2 GB ~1.9 llama.cpp Why
Qwen3.6 27B 27.8B Q6_K 21.2 GB 8.00 GB 29.8 GB +19.2 GB ~1.9 llama.cpp Why
Gemma 3 27B 27.4B Q6_K 20.9 GB 10.41 GB 31.9 GB +21.3 GB ~1.7 llama.cpp Why
Gemma 4 26B-A4B 26.5B MoE / 3.8B act Q6_K 20.2 GB 5.20 GB 26.0 GB +15.4 GB ~6.0 llama.cpp Why
Devstral Small 2 24B 24B Q6_K 18.3 GB 20.00 GB 38.9 GB +28.3 GB ~2.0 llama.cpp Why
Mistral Small 3.2 24B 23.6B Q6_K 18.0 GB 20.00 GB 38.6 GB +28.0 GB ~2.0 llama.cpp Why
gpt-oss 20B 20.9B MoE / 3.6B act MXFP4 10.8 GB 3.00 GB 14.4 GB +3.8 GB ~16 llama.cpp Why
Qwen3 14B 14.8B Q6_K 11.3 GB 20.00 GB 31.9 GB +21.3 GB ~3.2 llama.cpp Why
DeepSeek-R1-Distill-Qwen 14B 14.8B Q6_K 11.3 GB 24.00 GB 35.9 GB +25.3 GB ~3.2 llama.cpp Why
Qwen2.5-Coder 14B 14.8B Q6_K 11.3 GB 24.00 GB 35.9 GB +25.3 GB ~3.2 llama.cpp Why
Phi-4 14B 14.7B Q6_K 11.2 GB 3.13 GB 15.0 GB +4.4 GB ~6.7 llama.cpp Why
Ministral 3 14B 13.9B Q6_K 10.6 GB 20.00 GB 31.2 GB +20.6 GB ~3.4 llama.cpp Why
Gemma 3 12B 12.2B Q6_K 9.3 GB 8.31 GB 18.2 GB +7.6 GB ~4.6 llama.cpp Why
Mistral NeMo 12B 12.2B Q6_K 9.3 GB 20.00 GB 29.9 GB +19.3 GB ~3.9 llama.cpp Why
Gemma 4 12B 12B Q6_K 9.2 GB 8.31 GB 18.1 GB +7.5 GB ~4.7 llama.cpp Why
Qwen3.5 9B 9.65B Q6_K 7.4 GB 4.00 GB 12.0 GB +1.4 GB ~16 llama.cpp Why
Ornith 1.5 9B New this week 9.41B Q6_K 7.2 GB 4.00 GB 11.8 GB +1.2 GB ~17 llama.cpp Why
Ministral 3 8B 8.92B Q6_K 6.8 GB 17.00 GB 24.4 GB +13.8 GB ~5.3 llama.cpp Why
Granite 4.1 8B 8.79B Q6_K 6.7 GB 20.00 GB 27.3 GB +16.7 GB ~5.4 llama.cpp Why
Fara 7B 8.29B Q6_K 6.3 GB 6.84 GB 13.8 GB +3.2 GB ~9.9 llama.cpp Why
Qwen3 8B 8.19B Q6_K 6.3 GB 18.00 GB 24.9 GB +14.3 GB ~5.8 llama.cpp Why
Llama 3.1 8B Instruct 8.03B Q6_K 6.1 GB 16.00 GB 22.7 GB +12.1 GB ~5.9 llama.cpp Why
DeepSeek-R1-Distill-Qwen 7B 7.62B Q6_K 5.8 GB 7.00 GB 13.4 GB +2.8 GB ~11 llama.cpp Why
Qwen2.5-Coder 7B 7.62B Q6_K 5.8 GB 7.00 GB 13.4 GB +2.8 GB ~11 llama.cpp Why
Olmo 3 7B Instruct 7.3B Q6_K 5.6 GB 9.50 GB 15.7 GB +5.1 GB ~7.0 llama.cpp Why
Ministral 3 3B 3.85B Q6_K 2.9 GB 13.00 GB 16.5 GB +5.9 GB ~12 llama.cpp Why
Phi-4-mini 3.8B 3.84B Q6_K 2.9 GB 16.00 GB 19.5 GB +8.9 GB ~12 llama.cpp Why
Granite 4.1 3B 3.4B Q6_K 2.6 GB 10.00 GB 13.2 GB +2.6 GB ~14 llama.cpp Why
Llama 3.2 3B Instruct 3.21B Q6_K 2.5 GB 14.00 GB 17.1 GB +6.5 GB ~15 llama.cpp Why
Kimi K3 2.8T-A104B New 2780B MoE / 104B act Q6_K 2123.0 GB 3.38 GB 2127.0 GB +2116.4 GB ~0.2 llama.cpp Why
Qwen3.8 2.4T-A95B New 2446B MoE / 95B act Q6_K 1868.0 GB 11.50 GB 1880.1 GB +1869.5 GB ~0.2 llama.cpp Why
DeepSeek V4 Pro 1.6T-A49B New 1650B MoE / 49B act Q6_K 1260.1 GB 8.58 GB 1269.3 GB +1258.7 GB ~0.4 llama.cpp Why
Kimi K2.6 1T-A32B 1027B MoE / 32B act Q6_K 784.3 GB 8.58 GB 793.5 GB +782.9 GB ~0.6 llama.cpp Why
GLM-5.2 744B-A40B 753B MoE / 40B act Q6_K 575.1 GB 10.97 GB 586.6 GB +576.0 GB ~0.5 llama.cpp Why
DeepSeek-R1 671B 671B MoE / 37B act Q6_K 512.4 GB 8.58 GB 521.6 GB +511.0 GB ~0.5 llama.cpp Why
Qwen3.5 397B-A17B 403B MoE / 17B act Q6_K 307.8 GB 3.75 GB 312.1 GB +301.5 GB ~1.1 llama.cpp Why
Ornith 1.5 397B-A17B New this week 397B MoE / 17B act Q6_K 303.2 GB 3.75 GB 307.5 GB +296.9 GB ~1.1 llama.cpp Why
DeepSeek V4 Flash 284B-A13B New 284B MoE / 13B act Q6_K 216.9 GB 6.05 GB 223.5 GB +212.9 GB ~1.4 llama.cpp Why
Qwen3 235B-A22B 235B MoE / 22B act Q6_K 179.5 GB 23.50 GB 203.6 GB +193.0 GB ~0.8 llama.cpp Why
Qwen3.5 122B-A10B 125B MoE / 10B act Q6_K 95.5 GB 3.00 GB 99.1 GB +88.5 GB ~1.9 llama.cpp Why
Nemotron 3 Super 120B-A12B 124B MoE / 12B act Q6_K 94.7 GB 1.00 GB 96.3 GB +85.7 GB ~1.7 llama.cpp Why
Ling 3.0 Flash 124B-A5B New 124B MoE / 5.1B act Q6_K 94.7 GB 0.98 GB 96.3 GB +85.7 GB ~3.9 llama.cpp Why
Mistral Small 4 119B-A6B 119B MoE / 6.5B act Q6_K 90.9 GB 2.81 GB 94.3 GB +83.7 GB ~3.0 llama.cpp Why
gpt-oss 120B 117B MoE / 5.1B act MXFP4 60.5 GB 4.50 GB 65.6 GB +55.0 GB ~5.7 llama.cpp Why
Llama 4 Scout 109B-A17B 109B MoE / 17B act Q6_K 83.2 GB 7.13 GB 91.0 GB +80.4 GB ~1.1 llama.cpp Why

Totals = quantised weights + f16 KV cache at 128K tokens + 0.6 GB runtime overhead, against 10.6 GB usable VRAM (12 GB less display and driver reserve). Tokens per second are estimated from 384 GB/s peak memory bandwidth at batch 1 — not measured. Read the method.