Hardware profile

Current generation

AMD Ryzen AI Max+ 395 (Strix Halo) mini PC · 128 GB

128 GB shared CPU/GPU memory · 256 GB/s · verified

Platform Linux
Available for models 128 GB
Generation Current generation
Release date 2025
Backends Ollama, llama.cpp, ROCm
Memory bandwidth 256 GB/s
Last verified

usable GPU memory ~96-112GB depending on BIOS/OS; also 64GB variant This is a compact shared-memory system, not a dedicated-VRAM GPU. The audit warns that usable GPU memory may be roughly 96-112 GB depending on BIOS, OS, and allocation settings, so the full 128 GB should not be treated as universally available to one model.

Recommended quantization by model

This table chooses the highest-quality published quantization that still clears the selected 8K context estimate. It does not compare output quality or claim that every backend has the same kernels.

Model Recommended quantization Estimated requirement Context ceiling Result
Flint 40B Q8_0 44.0 GB at 8K 262,144 tokens Comfortable fit
NVIDIA Nemotron 3.5 Bolt E4B Q4_K_M 8.0 GB at 8K 65,536 tokens Comfortable fit
LFM3-1.7B Q8_0 3.4 GB at 8K 262,144 tokens Comfortable fit
Bonsai 2 PQ2_0 9.2 GB at 8K 262,144 tokens Comfortable fit
Qwen3.8 27B Q8_0 32.0 GB at 8K 262,144 tokens Comfortable fit
Gemma 4 12B Unified Q8_0 14.7 GB at 8K 262,144 tokens Comfortable fit
Gemma 4 E4B Q8_0 11.0 GB at 8K 131,072 tokens Comfortable fit
gpt-oss-20b MXFP4 13.8 GB at 8K 131,072 tokens Comfortable fit
Qwen3.6 35B-A3B Q8_0 39.5 GB at 8K 262,144 tokens Comfortable fit
Gemma 4 31B Q8_0 36.5 GB at 8K 262,144 tokens Comfortable fit
gpt-oss-120b MXFP4 65.2 GB at 8K 131,072 tokens Comfortable fit
Qwen3 8B Q8_0 11.6 GB at 8K 32,768 tokens Comfortable fit
DeepSeek R1 8B Q8_0 11.1 GB at 8K 131,072 tokens Comfortable fit
Llama 3.2 3B Q8_0 5.8 GB at 8K 131,072 tokens Comfortable fit
Phi-4 Mini Q8_0 6.7 GB at 8K 131,072 tokens Comfortable fit
Mistral 7B Q8_0 10.3 GB at 8K 32,768 tokens Comfortable fit
Gemma 3 4B Q8_0 7.6 GB at 8K 131,072 tokens Comfortable fit

Per-quantization fit for recent models

These are the five most relevant non-server models plus the next current model in the catalog. Each row uses the same 8K formula, so changing a quantization or context length produces an arithmetic result rather than a new benchmark claim.

Model Quantization Weight files 8K requirement Result 8K context ceiling Speed band Ollama
Flint 40B UD-IQ1_M 11.35 GB 13.1 GB Comfortable fit 262,144 tokens Estimate · Very fast relative band No verified tag
Flint 40B UD-IQ2_XXS 11.86 GB 13.6 GB Comfortable fit 262,144 tokens Estimate · Very fast relative band No verified tag
Flint 40B UD-Q2_K_XL 13.56 GB 15.3 GB Comfortable fit 262,144 tokens Estimate · Very fast relative band No verified tag
Flint 40B UD-IQ3_XXS 14.54 GB 16.3 GB Comfortable fit 262,144 tokens Estimate · Very fast relative band No verified tag
Flint 40B UD-Q3_K_XL 18.49 GB 20.2 GB Comfortable fit 262,144 tokens Estimate · Very fast relative band No verified tag
Flint 40B NVFP4 22.86 GB 24.6 GB Comfortable fit 262,144 tokens Estimate · Very fast relative band ollama run flint:40b
Flint 40B UD-Q4_K_XL 25.05 GB 26.8 GB Comfortable fit 262,144 tokens Estimate · Very fast relative band No verified tag
Flint 40B UD-Q5_K_XL 29.92 GB 31.7 GB Comfortable fit 262,144 tokens Estimate · Very fast relative band No verified tag
Flint 40B UD-Q6_K_XL 36.32 GB 38.1 GB Comfortable fit 262,144 tokens Estimate · Very fast relative band No verified tag
Flint 40B Q8_0 42.30 GB 44.0 GB Comfortable fit 262,144 tokens Estimate · Very fast relative band No verified tag
NVIDIA Nemotron 3.5 Bolt E4B Q4_K_M 6.18 GB 8.0 GB Comfortable fit 65,536 tokens Estimate · Fast relative band ollama run nemotron-3.5-bolt:e4b
LFM3-1.7B QAD-Q4_0 1.05 GB 2.7 GB Comfortable fit 262,144 tokens Estimate · Very fast relative band ollama run lfm3:1.7b-qad-q4_0
LFM3-1.7B Q4_K_M 1.10 GB 2.7 GB Comfortable fit 262,144 tokens Estimate · Very fast relative band ollama run lfm3:1.7b-q4_K_M
LFM3-1.7B Q5_K_M 1.26 GB 2.9 GB Comfortable fit 262,144 tokens Estimate · Very fast relative band No verified tag
LFM3-1.7B Q6_K 1.43 GB 3.0 GB Comfortable fit 262,144 tokens Estimate · Very fast relative band No verified tag
LFM3-1.7B Q8_0 1.85 GB 3.4 GB Comfortable fit 262,144 tokens Estimate · Very fast relative band ollama run lfm3:1.7b-q8_0
Bonsai 2 PTQ1_0 5.95 GB 8.0 GB Comfortable fit 262,144 tokens Estimate · Slow relative band No verified tag
Bonsai 2 PQ2_0 7.21 GB 9.2 GB Comfortable fit 262,144 tokens Estimate · Slow relative band No verified tag
Bonsai 2 Q2_0 7.63 GB 9.7 GB Comfortable fit 262,144 tokens Estimate · Slow relative band ollama run bonsai-2:27b-q2_0
Qwen3.8 27B Q4_K_M 17.39 GB 19.4 GB Comfortable fit 262,144 tokens Estimate · Slow relative band ollama run qwen3.8:27b-q4_K_M
Qwen3.8 27B Q8_0 29.98 GB 32.0 GB Comfortable fit 262,144 tokens Estimate · Slow relative band ollama run qwen3.8:27b-q8_0
Gemma 4 12B Unified Q4_0 7.15 GB 9.1 GB Comfortable fit 262,144 tokens Estimate · Moderate relative band ollama run gemma4:12b-it-qat
Gemma 4 12B Unified Q4_K_M 7.30 GB 9.2 GB Comfortable fit 262,144 tokens Estimate · Moderate relative band ollama run gemma4:12b-it-q4_K_M
Gemma 4 12B Unified Q8_0 12.85 GB 14.7 GB Comfortable fit 262,144 tokens Estimate · Moderate relative band ollama run gemma4:12b-it-q8_0

Speed bands are relative heuristics, not measured tokens per second. Verify the package name, license, backend support, and free memory before relying on a result.

Why this memory result is not a guarantee

AMD Ryzen AI Max+ 395 (Strix Halo) mini PC · 128 GB has 128 GB of shared CPU/GPU memory. The formula subtracts weight files, KV cache, and 1.5 GB of runtime overhead, then requires 20% remaining headroom for a comfortable result. Driver reservations, display buffers, other applications, longer prompts, concurrent requests, and backend-specific workspace can all reduce the usable budget.

Shared-memory AI systems may expose less memory to the GPU than the installed total. Treat 128 GB as an upper bound and verify the firmware allocation for the exact model and operating system.

Low-cost setup upgrades

Useful accessories around AMD Ryzen AI Max+ 395 (Strix Halo) mini PC · 128 GB

These optional setup upgrades address storage, cooling, or power resilience. None increases GPU or unified-memory capacity.

External NVMe SSD for model storage

Keeps large GGUF and MLX files off the boot drive. Fast storage reduces load time, but it does not increase the memory available for inference.

Search current listings on Amazon

Desktop RAM upgrade kit

Useful for MoE CPU offload and keeping the operating system out of VRAM. Match the motherboard's memory type, slot layout, capacity limit, and validated part numbers.

Search current listings on Amazon

GPU support bracket

A lower-cost mechanical upgrade for heavy three-slot cards. Check clearance, mounting height, and whether the bracket blocks fans or case panels.

Search current listings on Amazon

As an Amazon Associate I earn from qualifying purchases. Links are sponsored search links and do not change the price you pay. Affiliate disclosure.

Specific model checks

Compare current hardware

The closest current-generation profiles by memory capacity are below. A higher tier can increase the context ceiling or make a larger quantization comfortable, but it does not automatically guarantee faster generation.

Run the interactive check

Sources and verification

Data reviewed . Check the linked vendor material for the exact configuration before buying or installing.

FAQ

Questions about AMD Ryzen AI Max+ 395 (Strix Halo) mini PC · 128 GB.

How much shared CPU/GPU memory does AMD Ryzen AI Max+ 395 (Strix Halo) mini PC · 128 GB provide for local AI?

AMD Ryzen AI Max+ 395 (Strix Halo) mini PC · 128 GB is listed with 128 GB of shared CPU/GPU memory and 256 GB/s of memory bandwidth. The operating system, display buffers, and other applications share that capacity, so the model budget is always lower than the bare hardware number.

Which current local models fit comfortably on AMD Ryzen AI Max+ 395 (Strix Halo) mini PC · 128 GB?

Flint 40B, NVIDIA Nemotron 3.5 Bolt E4B, LFM3-1.7B. Comfortable means the 8K estimate leaves at least 20% headroom after weights, KV cache, and runtime overhead. A larger or higher-quality quantization may move an individual result into the tight band.

What context length can gpt-oss-120b at MXFP4 use on this machine?

At the selected quantization, the formula reaches 131,072 tokens before the machine's 128 GB capacity is exhausted. The model's native context limit still caps the result, and real workloads may run out earlier because of fragmentation, other applications, or backend workspace.

Is the 256 GB/s bandwidth figure a measured token speed?

No. Fast relative band is a relative estimate based on active parameters and memory bandwidth. It is not a benchmark: backend kernels, batch size, thermals, CPU offload, and concurrent work can change real generation speed substantially.

What should I do if a model does not fit on AMD Ryzen AI Max+ 395 (Strix Halo) mini PC · 128 GB?

Try a lower-bit published quantization and a shorter context first. If the minimum requirement still exceeds 128 GB, the arithmetic gap to a 20% comfort target is not available until a model exceeds this capacity. Compare another current hardware profile with more memory before upgrading.