Model × hardware check
Can Gemma 4 31B run on AMD Radeon RX 9070 XT · 16 GB?
No, the selected package does not fit at 8,192 tokens. a workstation-class dense model with a much larger memory footprint The RX 9070 XT provides 16 GB of VRAM with 640 GB/s of memory bandwidth; ROCm support still depends on the runtime and kernel.
Short answer
Won't fit
The estimate is below the minimum memory requirement. Choose a smaller model, a lower-bit quantization, or a machine with more usable memory.
- Available VRAM
- 16 GB
- Estimated requirement
- 22.2 GB
- Headroom
- -6.2 GB
- Fit ratio
- 72%
- Recommended quantization
- Q4_K_M
- Context ceiling
- 0 tokens
- Speed estimate
- Estimate · Moderate relative band
What the numbers say
The selected Gemma 4 31B package uses 19.5 GB of weight files. The 8K KV cache estimate is 1.2 GB, and the formula adds 1.5 GB of runtime overhead. That produces a 22.2 GB requirement against 16 GB of VRAM.
Current-generation discrete GPU profile. VRAM is the hard capacity limit; system RAM is separate and relevant only when the runtime supports offload.
The context ceiling shown above is the point where the same formula reaches the machine's capacity. It is not a promise that the backend can allocate that full context after the operating system and other applications take their share.
Quantization trade-offs at 8K
| Quantization | Weight files | 8K requirement | Fit on this machine | Context ceiling | Speed estimate | Ollama |
|---|---|---|---|---|---|---|
| Q4_K_M | 19.52 GB | 22.2 GB | Won't fit · 72% | 0 tokens | Estimate · Moderate relative band | ollama run gemma4:31b-it-q4_K_M |
| Q8_0 | 33.84 GB | 36.5 GB | Won't fit · 44% | 0 tokens | Estimate · Moderate relative band | ollama run gemma4:31b-it-q8_0 |
Run commands
ollama run gemma4:31b-it-q4_K_Mlms get "Gemma 4 31B"@q4_k_m
lms load <model-key-from-lms-ls> --gpu max --context-length 8192llama-cli -hf google/gemma-4-31B-it -c 8192 -ngl 99 -p "Your prompt"mlx_lm.generate --model google/gemma-4-31B-it --prompt "Your prompt" --max-tokens 8192Commands are examples, not a guarantee that the selected quantization tag is available in every runtime. Confirm the package name and license on the linked model page.
If it does not fit
Needs about 10.6 GB more VRAM for comfort
The calculator targets 20% headroom, so the practical upgrade target is approximately 26.6 GB of VRAM, not just the bare 22.2 GB minimum.
Low-cost setup upgrades
Useful upgrades around AMD Radeon RX 9070 XT · 16 GB
These are optional setup improvements, not a claim that an accessory can increase 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 AmazonDesktop 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 AmazonGPU 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 AmazonAs an Amazon Associate I earn from qualifying purchases. Links are sponsored search links and do not change the price you pay. Affiliate disclosure.
Where this estimate can break
- A Q4 build plus KV cache is a workstation-class workload, not a typical 16 GB laptop fit.
- The GGUF package needs the multimodal projector for image input.
- Other GPU applications, display buffers, and the operating system reduce usable memory.
- Longer prompts, concurrent requests, and a different backend can raise peak memory.
Compare this pairing
FAQ
Questions about this pairing.
How much memory does Gemma 4 31B need on AMD Radeon RX 9070 XT · 16 GB?
At an 8K context with Q4_K_M, the estimate is 22.2 GB: 19.5 GB of weights, 1.2 GB of KV cache, and 1.5 GB of runtime overhead. The available VRAM is 16 GB.
What context length can AMD Radeon RX 9070 XT · 16 GB handle with this model?
The calculated ceiling is 0 tokens for this quantization, capped by the model's native 262,144-token context. Actual usable context can be lower after the OS, other applications, and backend workspace.
How does quantization change the memory requirement on AMD Radeon RX 9070 XT · 16 GB?
At 8,192 tokens, the published variants calculate as follows: Q4_K_M: 22.2 GB, won't fit; Q8_0: 36.5 GB, won't fit. A lower-bit file can move a result from too large to tight, but quality and kernel support may differ.
What can I run if Gemma 4 31B does not fit on AMD Radeon RX 9070 XT · 16 GB?
Reaching the 20% comfort threshold would need about 10.6 GB more VRAM. Models that fit this machine in the current catalog include Flint 40B, NVIDIA Nemotron 3.5 Bolt E4B, LFM3-1.7B.
Is the speed estimate for Gemma 4 31B on AMD Radeon RX 9070 XT · 16 GB measured?
No. Moderate relative band is a heuristic band derived from 30.7B active parameters and 640 GB/s published memory bandwidth. Backend kernels, batch size, thermals, and CPU offload can change actual tokens per second.