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Qwen3.5-Unsloth-GGUF-R9700-Benchmark
JohnTdi/Qwen3.5-Unsloth-GGUF-R9700-Benchmark
Qwen3.5-Unsloth-GGUF-R9700-Benchmark is a machine learning model from JohnTdi. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Exact GGUF files used in the Comprehensive LLM Benchmark on AMD Radeon AI PRO R9700 (RDNA4).
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Mar 27, 2026
- Updated
- Mar 27, 2026
- SHA
- c2dd4ad0
Model card
From the Hugging Face model README
Qwen3.5 GGUF Models — RDNA4 R9700 Benchmark
Exact GGUF files used in the Comprehensive LLM Benchmark on AMD Radeon AI PRO R9700 (RDNA4).
These files are provided so anyone with an R9700 can reproduce the results exactly.
Note: The 35B file was downloaded from unsloth/Qwen3.5-35B-A3B-GGUF on 2025-02-25. Unsloth has since updated the file — the current version on their repo is larger (20.71 GiB vs 18.34 GiB). This repo preserves the original file used in the benchmark.
Models
| Model | Type | Total Params | Active/Token | File Size | Quantization | Source |
|---|---|---|---|---|---|---|
| Qwen3.5-35B-A3B | MoE | 34.66B | ~3.5B | 18.34 GiB | UD-Q4_K_XL (file_type=Q4_K_M) | unsloth |
| Qwen3.5-27B | Dense | 26.90B | 26.90B | 15.59 GiB | Q4_K_M | unsloth |
System Configuration
| Component | Details |
|---|---|
| GPU | AMD Radeon AI PRO R9700 (gfx1201, RDNA4, 32 GB GDDR6, 64 CUs) |
| Memory bandwidth | 640 GB/s (MCLK 1258 MHz) |
| PCIe | PCIe 5.0 x16, 32 GT/s |
| CPU | AMD Ryzen 9 9900X 12-Core |
| RAM | 64 GB DDR5 |
| OS | Ubuntu 24.04.4 LTS, Kernel 6.19.8 |
| Mesa (RADV) | 25.2.8 |
| llama.cpp | commit dc8d14c58 (build 8554) |
Best Results
Qwen3.5-35B-A3B (MoE)
| Metric | RADV | AMDVLK |
|---|---|---|
| Best decode | 149.5 t/s | 163.7 t/s (gfx+rm_kq=1) |
| Best prefill pp2048 | 3,075 t/s (ub=2048) | 2,170 t/s |
Qwen3.5-27B (Dense)
| Metric | RADV | AMDVLK |
|---|---|---|
| Best decode | 32.5 t/s (ASPM perf) | 33.2 t/s (ASPM perf) |
| Best prefill pp2048 | 993 t/s (Mesa 25.3.6) | 207 t/s |
Key Findings
rm_kq=1is the single most impactful code change: +1% RADV, +2% AMDVLK MoE, +13% AMDVLK dense- PCIe ASPM=performance gives +10.8% dense decode on RADV
- gfx queue helps AMDVLK MoE (+4.7%) but hurts AMDVLK dense (-8%)
- RADV wins overall (best prefill, competitive decode)
- Dense models reach 79-83% bandwidth utilization with optimizations
Full Results
See BENCHMARK_COMPREHENSIVE_R9700.md for the complete benchmark with 50+ configurations tested.
License
Apache 2.0 (following the original model license).
Credits
- License
- apache-2.0
- Languages
- en
- Created
- Mar 27, 2026
- Updated
- Mar 27, 2026