Hardware · AMD

What AI models can the AMD Ryzen AI 7 350 (Radeon 860M) (16 GB) run?

Unified memory
16.0 GB
Usable for models
12.0 GB
Memory bandwidth
120 GB/s
FP16 compute
12.3 TFLOPS
Released
2025
397 / 622 LLMs run Best: Mellum2.1 Thinking (12B-A2.5B) 54 / 61 Image models run Best: FLUX.2 [klein] 4B 14 / 43 Video models run Best: LTX-Video 2B 65 / 70 Decision models run Best: Jina Reranker v3.5

macOS lets the GPU use roughly two-thirds to three-quarters of unified memory by default, so we plan around that figure rather than the full 16.0 GB.

More about this hardware

MakerAMD
TypeUnified-memory system on a chip
GPU share of memory75% (what the GPU can typically be given for a model)
ChipAMD Ryzen AI 7 350 (Radeon 860M)

Apps that run models well on the AMD Ryzen AI 7 350 (Radeon 860M) (16 GB)

Windows

  1. LemonadeBuilt for Ryzen AI and Strix Halo, including NPU + iGPU modes on Windows.
  2. LM StudioPoint-and-click: search, download and chat in one window.
  3. OllamaOne command with Ollama’s own build of this model.
  4. llama.cppUsually the first to support new model architectures.

Linux

  1. LemonadeBuilt for Ryzen AI and Strix Halo, including NPU + iGPU modes on Windows.
  2. LM StudioPoint-and-click: search, download and chat in one window.
  3. OllamaOne command with Ollama’s own build of this model.
  4. llama.cppUsually the first to support new model architectures.

For a typical model that fits in memory. Each model page picks the best app for that model on this hardware. All apps

Best LLMs for the AMD Ryzen AI 7 350 (Radeon 860M) (16 GB)

Quality Model Quant Memory Speed Runs
66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 84/100 (quality, fit, speed and memory use) sets the ranking. Mellum2.1 Thinking (12B-A2.5B)JetBrains Q4_K_M 9.1 GB 43.3 tok/s Runs great
78Great quality (A) · 78 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 12BGoogle Q4_K_M 9.5 GB 10.6 tok/s Runs well
76Great quality (A) · 76 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. K2 Horizon 7BInstitute of Foundation Models Q4_K_M 8.3 GB 14.1 tok/s Runs well
60Good quality (B) · 60 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. Ling 3.0 Tiny (8B-A1.3B)Ant Group (inclusionAI) Q8_0 10.1 GB 41.8 tok/s Runs great
74Great quality (A) · 74 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. SenseNova Loop 9B PreviewSenseTime Q4_K_M 7.9 GB 13.1 tok/s Runs well
74Great quality (A) · 74 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. MiMo V2.6 Distill Qwen 9BXiaomi Q4_K_M 7.6 GB 13.5 tok/s Runs well
73Great quality (A) · 73 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.5 9BDeepReinforce Q4_K_M 7.7 GB 13.1 tok/s Runs well
72Great quality (A) · 72 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 9BAlibaba Q4_K_M 7.7 GB 13.1 tok/s Runs well
71Great quality (A) · 71 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.0 9BDeepReinforce Q4_K_M 7.7 GB 13.1 tok/s Runs well
58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Maple Preview (20B-A1B)DeepGrove Q3_K_M 11.6 GB 81.1 tok/s Runs welltight fit
66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Nemotron 3.5 Bolt E4BNVIDIA Q4_K_M 6.6 GB 28.2 tok/s Runs well
70Great quality (A) · 70 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. TMax 9BAi2 Q4_K_M 7.3 GB 14.2 tok/s Runs well

Best Image models for the AMD Ryzen AI 7 350 (Radeon 860M) (16 GB)

Quality Model Quant Memory Speed Runs
76Great quality (A) · 76 of 100: how capable the model is at FP8, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 4BBlack Forest Labs FP8 10.2 GB 5.6 s Runs great
78Great quality (A) · 78 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 86/100 (quality, fit, speed and memory use) sets the ranking. Z-Image TurboAlibaba (Tongyi) Q4 GGUF 10.1 GB 19 s Runs well
89Excellent quality (A+) · 89 of 100: how capable the model is at FP8, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. FLUX 3 Image KleinBlack Forest Labs FP8 7.9 GB 34 s Runs wellencoder unloaded after use
79Great quality (A) · 79 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 83/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-Image TurboBaidu Q4 GGUF 11.3 GB 24 s Runs welltight fit
78Great quality (A) · 78 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 82/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 9BBlack Forest Labs Q4 GGUF 8.0 GB 14 s Runs wellencoder unloaded after use
58Good quality (B) · 58 of 100: how capable the model is at FP16, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. DreamShaper XL v2 TurboLykon FP16 8.9 GB 8.1 s Runs great

Best Video models for the AMD Ryzen AI 7 350 (Radeon 860M) (16 GB)

Quality Model Quant Memory Speed Runs
49Fair quality (C) · 49 of 100: how capable the model is at FP8, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. LTX-Video 2BLightricks FP8 10.8 GB 2.3 min Runs welltight fit
44Fair quality (C) · 44 of 100: how capable the model is at FP8, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 2BZhipu AI FP8 11.0 GB 5.6 min Runs welltight fit
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 5BZhipu AI FP8 9.6 GB 17.7 min Slowencoder unloaded after use
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 5B I2VZhipu AI FP8 10.2 GB 17.7 min Slowencoder unloaded after use
83Great quality (A) · 83 of 100: how capable the model is at FP8, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. Bernini-R A14B (video generation + editing)ByteDance FP8 10.7 GB 87.9 min Very slowtight fit · CPU offload

Best Decision models for the AMD Ryzen AI 7 350 (Radeon 860M) (16 GB)

Quality Model Quant Memory Speed Runs
86Excellent quality (A+) · 86 of 100: how capable the model is at F16, whatever it runs on. Match score 93/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3.5Jina AI F16 3.0 GB 64 ms Runs great
84Great quality (A) · 84 of 100: how capable the model is at F16, whatever it runs on. Match score 92/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3Jina AI F16 3.0 GB 64 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking. FRIDA-DecisionsSber AI F16 2.4 GB 38 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 DecideFastino F16 1.7 GB 25 ms Runs great
80Great quality (A) · 80 of 100: how capable the model is at F16, whatever it runs on. Match score 91/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 0.6BAlibaba F16 3.0 GB 64 ms Runs great
82Great quality (A) · 82 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. mxbai-rerank-large v2Mixedbread Q8_0 3.3 GB 131 ms Runs great
76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. Llama Prompt Guard 2 86MMeta F16 1.2 GB 27 ms Runs great
76Great quality (A) · 76 of 100: how capable the model is at F16, whatever it runs on. Match score 89/100 (quality, fit, speed and memory use) sets the ranking. mxbai-rerank-base v2Mixedbread F16 2.6 GB 53 ms Runs great

Best LLMs by task on this hardware Open in Model Finder

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.

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