Qwen3.5 35B Q4 VRAM Requirement and Ollama Model Size
Qwen3.5 35B Q4 needs 22GB minimum VRAM, 24GB optimal VRAM, and 32GB+ system RAM for a safer Ollama run. Top-20 curated profile from ollama.com popular list.. Caveat: Estimated values are placeholders unless marked measured..
Hardware Snapshot
| Family | Qwen3.5 |
|---|---|
| Scenario | reasoning |
| License scope | open-source |
| Quantization | Q4 |
| VRAM minimum | 22GB |
| VRAM optimal | 24GB |
| Best local GPU | RTX 3090 24GB |
| Cloud fallback | A6000 48GB |
| Updated | 2026-02-24 |
| Data status | Verified by Real Hardware |
| Ollama source | Library reference (verified: 2026-02-24) |
| Ollama tag | qwen3.5:35b |
| Popularity | New Popular Model |
| Category | Reasoning |
Benchmark Anchors
| Hardware | Expected tok/s |
|---|---|
| RTX 3090 24GB | 6.8 |
| RTX 4090 24GB | 9.2 |
| A100 80GB | 16.3 |
Quick Answers
- How much VRAM does Qwen3.5 35B Q4 need?
- Qwen3.5 35B Q4 needs about 22GB minimum VRAM and 24GB optimal VRAM for a safer local run target.
- Can Qwen3.5 35B Q4 run on an RTX 3090 24GB?
- Yes. Qwen3.5 35B Q4 fits comfortably on an RTX 3090 24GB target with 24GB optimal VRAM.
- What is the Ollama command for Qwen3.5 35B Q4?
- Use ollama run qwen3.5:35b. Check the Ollama tag qwen3.5:35b before running.
- What is the approximate Ollama model size for Qwen3.5 35B Q4?
- Qwen3.5 35B Q4 uses the qwen3.5:35b Ollama tag. Treat the Q4 35 profile as smaller than the runtime VRAM budget; use 22GB minimum VRAM and 24GB optimal VRAM as the safer sizing numbers.
- How much system RAM does Qwen3.5 35B Q4 need in Ollama?
- Plan for at least 32GB system RAM alongside 22GB minimum VRAM and 24GB optimal VRAM. More RAM helps if layers spill to CPU or if you run multiple models.
- What is the RAM vs VRAM requirement for Qwen3.5 35B Q4?
- Qwen3.5 35B Q4 should be sized by GPU VRAM first: 22GB minimum and 24GB optimal. System RAM should be at least 32GB so Ollama has room for CPU-side layers, context, and the surrounding app process.
- What is Qwen3.5 35B Q4 VRAM usage on an RTX 3090?
- Qwen3.5 35B Q4 is comfortable for an RTX 3090 24GB target. The page estimates 22GB minimum and 24GB optimal VRAM, with spill risk marked as moderate at long context.
- Which LocalVRAM profiles share the qwen3.5:35b Ollama tag?
- LocalVRAM tracks these profiles for the same Ollama tag or model family: Qwen3.5 35B Q4 (Q4, 22GB min/24GB optimal); Qwen3.5 35B Q5 (Q5, 24GB min/26GB optimal); Qwen3.5 35B Q8 (Q8, 44GB min/54GB optimal); Qwen3.5 35B FP16 (FP16, 50GB min/62GB optimal). Use the table on this page to compare quantization and VRAM targets before choosing a run command.
- Is Qwen3.5 35B Q4 benchmark data measured or estimated?
- Qwen3.5 35B Q4 has a verified RTX 3090 result of 2.778 tokens/s from LocalVRAM benchmark data.
Ollama Model Size and RAM Notes
| Ollama tag | qwen3.5:35b |
|---|---|
| Run command | ollama run qwen3.5:35b |
| Model size guidance | Q4 quantization, 35 profile; size runtime by VRAM, not download size alone |
| Runtime VRAM target | 22GB minimum, 24GB optimal |
| System RAM planning | 32GB or more when running this tag locally with Ollama |
Download size alone is not a safe runtime budget. Runtime memory also includes KV cache, context length, and GPU layer placement.
Ollama RAM vs VRAM Requirements
| GPU VRAM usage estimate | 22GB minimum / 24GB optimal |
|---|---|
| System RAM requirement | 32GB or more for Ollama runtime headroom |
| RTX 3090 24GB fit | Comfortable |
| CPU spill risk | Moderate at long context |
| Context warning | Longer context increases KV cache memory, so real VRAM usage can exceed short-prompt estimates. |
For Ollama, VRAM is the first fit check. System RAM matters when layers spill to CPU, when context grows, or when the local app stack runs beside the model.
Available Tag Variants and VRAM Targets
| Profile | Quantization | VRAM target | Ollama tag |
|---|---|---|---|
| Qwen3.5 35B Q4 | Q4 | 22GB min / 24GB optimal | qwen3.5:35b |
| Qwen3.5 35B Q5 | Q5 | 24GB min / 26GB optimal | qwen3.5:35b |
| Qwen3.5 35B Q8 | Q8 | 44GB min / 54GB optimal | qwen3.5:35b |
| Qwen3.5 35B FP16 | FP16 | 50GB min / 62GB optimal | qwen3.5:35b |
Ollama library tags often group multiple quantization choices under one model family. LocalVRAM separates them into VRAM profiles so you can pick the right local target.
Real Hardware Benchmark (RTX 3090)
| Tokens/s | 2.778 |
|---|---|
| Latency | 37551 ms |
| Prompt tokens | 31 |
| Eval tokens | 96 |
| Test time | 2026-06-24T06:22:37Z |
| GPU model | NVIDIA GeForce RTX 3090 |
Verified by real hardware.
Performance Curve
Reference anchors are baseline estimates. Measured RTX 3090 data is overlaid when available.
Best Hardware for Qwen3.5 35B Q4
- Local run: RTX 3090 (24GB) (Check latest deal) for around 2.778 tok/s on this profile.
- Cloud run: RunPod A6000 48GB , about 5.9x the local 3090 speed anchor.
- Alternative cloud: Vast.ai options for flexible spot pricing.
Local vs Cloud Cost Hint
| Mode | 40h / month | 120h / month |
|---|---|---|
| Local power only (3090 baseline) | $2.24 | $6.72 |
| A6000 48GB | $30.4 | $91.2 |
Related Model Profiles
- Qwen3.5 35B Q5 24GB min, 26GB optimal
- Qwen3.5 35B Q8 44GB min, 54GB optimal
- Qwen3.5 35B FP16 50GB min, 62GB optimal
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