Can RTX 5090 32GB run Qwen3-VL 8B?
Measured results for Qwen3-VL 8B (8.77B dense) on RTX 5090 32GB, plus what fits and the commands to run it.
Short answer
Yes. Qwen3-VL 8B Q8_0 fits fully on RTX 5090 32GB at 16k context, using 11.1 of 31.0 GB usable, and generates about 166.5 tokens/s in our own run. As the context fills it slows down: 131.3 tok/s with 16k tokens already in context (79% of the empty-context speed), measured. For Q8_0, our bandwidth-only estimate was ~113 tok/s against a measured median of ~167 (32% too pessimistic).
Measured generation speed by quantization
| Quant | Generation tok/s | Range | Prompt tok/s | Runs | Origin |
|---|---|---|---|---|---|
| Q4 class (median) | 242.4 | 242.4–242.4 | 12303 | 1 | includes our runs |
| Q8 class (median) | 166.5 | 166.5–166.5 | 12639 | 1 | includes our runs |
| Q4_K_M (our run, depth 0) | 242.4 | 3 repeats | 12303 | 3 | own measurement |
| Q8_0 (our run, depth 0) | 166.5 | 3 repeats | 12639 | 3 | own measurement |
Generation = tg128 (128 generated tokens, short context). Public rows are medians of community llama.cpp results (sources); our own runs use llama-bench b11658 on a rented GPU.
Speed vs context depth measured
Our own llama-bench runs on GeForce RTX 5090 (flash attention on, 3 repeats): generation and prompt speed with the given number of tokens already in the context.
| Quant | Context depth | Generation tok/s | vs depth 0 | Prompt tok/s |
|---|---|---|---|---|
| Q4_K_M | 0 | 242.4 | 100% | 12303 |
| Q4_K_M | 4k | 217.4 | 90% | 11283 |
| Q4_K_M | 16k | 173.8 | 72% | 8221 |
| Q8_0 | 0 | 166.5 | 100% | 12639 |
| Q8_0 | 4k | 154.6 | 93% | 11507 |
| Q8_0 | 16k | 131.3 | 79% | 8351 |
Alternatives
Less memory that still fits Qwen3-VL 8B
Smaller memory usually means a cheaper card or Mac (we do not list prices).
- Mac mini / iMac M4 16GB: Q4_K_M, 11 GB usable, ~16 tok/s scaled from measured
- RTX 5070 12GB: Q6_K, 11 GB usable, ~94 tok/s scaled from measured
- RTX 4070 12GB: Q6_K, 11 GB usable, ~71 tok/s scaled from measured
Other models on RTX 5090 32GB, similar size
- Gemma 4 E4B (hardware page): Q8_0, fits fully, ~177 tok/s (scaled from measured)
- Qwen3.5 9B: Q8_0, fits fully, ~156 tok/s (measured)
- Ornith 1.5 9B (hardware page): Q8_0, fits fully, ~145 tok/s (scaled from measured)
- DeepSeek R1 Distill Qwen 7B (hardware page): Q8_0, fits fully, ~179 tok/s (scaled from measured)
Memory and context limits
Q8_0 weights are 8.7 GB; the 16k f16 KV cache adds 2.42 GB. Largest context that fits in 31.0 GB usable:
| KV cache type | Max context |
|---|---|
| f16 | 128k |
| q8_0 | 256k |
| q4_0 | 512k |
Native limit 256k, 1M with YaRN. Full KV cache table for Qwen3-VL 8B.
Copy-paste commands
The advisor's pick for this hardware: Q8_0, 16k context.
llama-server -hf unsloth/Qwen3-VL-8B-Instruct-GGUF:Q8_0 -c 16384 -fa on --jinja -ngl 99
OLLAMA_CONTEXT_LENGTH=16384 ollama serve ollama run hf.co/unsloth/Qwen3-VL-8B-Instruct-GGUF:Q8_0
FAQ
How fast is Qwen3-VL 8B on RTX 5090 32GB?
About 166.5 tokens/s for generation (Q8_0 on llama.cpp CUDA, 128-token generation), 12639 tokens/s for prompt processing. Speed drops as the context fills; see the depth table.
How much memory does Qwen3-VL 8B need on RTX 5090 32GB?
The advisor's pick, Q8_0, is 8.7 GB of weights plus 2.42 GB of KV cache at 16k context (11.1 GB), against 31.0 GB usable.
Is the Qwen3-VL 8B speed on RTX 5090 32GB measured or estimated?
Measured: our own llama-bench run on a rented GeForce RTX 5090, including runs with 4k to 16k tokens already in context.
What can I use instead of RTX 5090 32GB for Qwen3-VL 8B?
With less memory, Mac mini / iMac M4 16GB (~16 tok/s), RTX 5070 12GB (~94 tok/s), RTX 4070 12GB (~71 tok/s) also fit it fully.
What is the maximum context for Qwen3-VL 8B on RTX 5090 32GB?
With an f16 KV cache about 128k tokens, 256k with q8_0 and 512k with q4_0, bounded by the model's own limit.
Related
All models on RTX 5090 32GB · Qwen3-VL 8B on all hardware · VRAM tier · all measured pages · leaderboard
Compare: RTX 4090 24GB vs RTX 5090 32GB · RTX 3090 24GB vs RTX 5090 32GB · 2x RTX 3090 (48GB total) vs RTX 5090 32GB