Qwen3.5-0.8B VRAM: 1GB, 2GB or 4GB?

Short answer: treat 1GB as a constrained Q4 experiment, 2GB as the practical quantized tier but a tight BF16 boundary, and 4GB as the safer tier for Qwen’s official 1.747GB BF16 checkpoint and multimodal runtime state. Qwen3.5-0.8B is natively multimodal, so a GGUF image/video deployment needs the matching projector as well as the language file.

Qwen3.5-0.8B files and practical tiers

Deployment path	Displayed files	Combined size	Planning tier
Community Q4_K_M + F16 projector	0.533GB + 0.205GB	0.738GB	1GB constrained; 2GB practical
Community Q8_0 + F16 projector	0.812GB + 0.205GB	1.017GB	1GB does not hold the files; 2GB practical
Official Qwen BF16 safetensors	One shard	1.747GB	2GB tight; 4GB safer

Why 1GB is only a constrained Q4 experiment

The community Q4 language file plus F16 projector totals 0.738GB, leaving roughly 0.26GB of nominal space on a 1GB device before cache, hybrid-attention state, vision processing, compute buffers, allocator behavior or display use. The Q8 pair already exceeds 1GB. Offload can allow launch on some systems, but that is not a whole-model 1GB GPU fit and does not establish usable latency.

Hybrid attention: calculate only the full-attention component

Qwen’s official configuration lists 24 language layers arranged as six repetitions of three linear-attention layers followed by one full-attention layer. That yields 18 linear-attention layers and six full-attention layers. The full-attention blocks use two KV heads with a 256-element head dimension.

With FP16/BF16 keys and values, the sequence-linear full-attention component is 2 × 6 × 2 × 256 × 2 = 12,288 bytes, or 12KiB per allocated token. Do not apply a conventional KV-cache formula to all 24 layers: the linear-attention layers maintain implementation-dependent recurrent and convolution state.

Allocated tokens	Full-attention KV payload only
8K	0.09375GiB
32K	0.375GiB
64K	0.75GiB
128K	1.5GiB
256K native maximum	3GiB

Edge-device safeguards

• Projector: include the conversion’s 0.205GB F16 projector for image/video inference.
• Vision: text-only output does not prove projector or image preprocessing compatibility.
• Runtime: runtime code and buffers can be large relative to a sub-1GB weight file.
• Context: native 256K capability is not a promise that an edge device can allocate that workload.
• Memory type: unified memory and system RAM are not dedicated VRAM; report placement and offload.
• Use case: validate output quality for the actual task; small size does not establish suitability.

Qwen3.5-0.8B versus Qwen3.5-2B

The Qwen3.5-2B guide covers a larger sibling whose community Q4-plus-projector pair is 1.949GB and official BF16 checkpoint is 4.548GB. Both use a 24-layer 3:1 hybrid attention pattern, but equal cache geometry does not mean equal total memory, speed, quality or visual accuracy.

Reproducible Qwen3.5-0.8B fit test

1. Record the first-party repository, conversion repository, revisions, every file and checksum.
2. Record runtime/version and verify hybrid-attention plus image/video support.
3. Record weight, projector, full-attention KV and linear-state precision.
4. Record device placement, offload and kernel/fallback path.
5. Fix text allocation, image/video workload, output target and concurrency.
6. Measure accelerator and system memory before load, after load, after vision encoding and at peak generation.
7. Capture preprocessing time, time to first token, throughput, fallback and errors.

Continue with the Qwen3-VL 2B comparison, small-model sizing guide, multimodal VRAM hub, Start Here, VRAM calculator, workload test, benchmark submission or all guides and tools.

Sources and limits

• Qwen official Qwen3.5-0.8B repository
• Qwen official configuration
• Qwen official BF16 index
• Unsloth community GGUF conversion
• HighVRAM methodology

Reviewed October 25, 2026. Repository file sizes were summed directly. Qwen’s BF16 checkpoint and configuration are first-party; GGUF/projector sizes are from the separately labeled Unsloth conversion. HighVRAM has not independently benchmarked every runtime, kernel, conversion, quantization or multimodal workload. File size is not peak resident memory.

Compare the family: use the Qwen3.5 VRAM hub to compare complete file totals, practical tiers and hybrid-cache geometry from 0.8B through 35B-A3B.