Qwen3.5

Qwen3.5-27B

Dense vision-language checkpoint with 64 text layers: 48 gated DeltaNet linear-attention layers and 16 full-attention layers, plus float32 recurrent state. Official vLLM guidance lists a 65 GB BF16 minimum and suggests one H200 or two H100 GPUs; its explicit verified hardware is Intel Arc Pro at shorter context. Candidate GPU fit and aggregate output capacity remain unverified.

Profile checked Oct 12, 2026 · Official model page ↗

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Parameters: 27.8B
Context: 262144
BF16 weights + cacheOverhead additional: Estimate unavailable

Workload memory estimate

Parallel active users means one simultaneous request per user. Include input and expected output in the token allowance; idle users do not count. This sizes memory, with response speed still unverified.

Pinned checkpoint and cache configuration have not been supplied.

This is a single-GPU model-and-cache scenario. Distributed model sizing is not evaluated here. Runtime and allocator overhead are additional. This subtotal does not guarantee GPU compatibility. Input and output both contribute to cached tokens. No offloading, shared prefixes or cache quantization is assumed.

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Supported deployment evidence

The finder evaluates exact, freshly documented rental configurations. Original BF16 is the default; quantized alternatives require opt-in. A profile describes sourced compatibility and memory allocation, with response speed and live stock assessed separately.

Sizing evidence is missing for deployment-aware search. An empty result does not establish that this model cannot run.

Hardware evidence

Benchmarked GPU profiles

Benchmark GPU / count	Architecture	VRAM per GPU	Matching on-demand instance
No benchmarked GPU profiles are available yet.

Measured performance

Inference benchmarks

Model	GPU setup	Engine	Quant.	Workload	Reported tok/s	Evidence	Max-load capacity scenarioUSD / million output tokens
No benchmark records have been supplied yet.