Best larger-system route
Studio 96
The smallest system in the range that reaches this model's preferred working allowance.
Explore Studio 96Qwen model
Qwen3.5 27B Hardware Requirements & Server Compatibility
Qwen3.5 27B is a current Qwen release for higher-quality multimodal reasoning, coding and document work. The pinned repository contains approximately 55.563GB of model weights. Our 64GB on one GPU figure is a calculated memory screen, while 96GB on one GPU is the safer starting allowance for deployment testing.
- Model version
Qwen/Qwen3.5-27B- Family and variant
- Qwen3.5 · 27B
- Source version
fc05daec18b0- Source updated
- 24 April 2026
Qwen Qwen3.5 27B
Qwen/Qwen3.5-27B - Minimum GPU memory
- 64GB on one GPU
- Recommended hardware
- 96GB on one GPU
- Licence
- Apache License 2.0
- Useful for
- Language & reasoning, Coding & agents, Vision & OCR
Buyer verdict
Where Qwen3.5 27B is a sensible fit
Shortlist Qwen3.5 27B when higher-quality multimodal reasoning, coding and document work is the priority and the exact licence and runtime suit the organisation. Choose hardware from the recommended allowance, then measure quality and performance on representative work before purchase.
These figures apply to the named model version. Quantisation, fine-tuning, context length, image resolution, batch size and serving software can materially change the hardware needed.
Hardware requirements
- Minimum
- 64GB on one GPU
- Recommended
- 96GB on one GPU
This allowance is derived from the pinned artifact and leaves only limited runtime headroom.
This working allowance creates room for runtime allocations and representative workload testing; it is not a performance benchmark.
Technical specification
Qwen3.5 27B model and hardware facts
Specifications shown for source version
fc05daec18b0a78c049392ed2e771dde82bdf654, updated
24 April 2026.
- Architecture
- Dense vision-language causal model
- Parameters
- 27B language model plus vision encoder
- Context
- 262,144 tokens native; extensible to 1,010,000 Architecture ceiling; serving capacity requires testing
- Modalities
- Text + image → text
- Repository weights
- 55.563GB Pinned first-party repository file total
- Native format
- BF16 safetensors
Product compatibility
Qwen3.5 27B compatibility across all 11 GPU systems
- Systems that fit without model splitting
- 7
- Systems needing multi-GPU validation
- 0
A system is listed as fitting when its GPU memory meets the requirement shown above. Speed, usable context, batch size and concurrent users still need testing with the final model and software configuration.
sme workstation
Team 32
- Per GPU
- 32GB
- Total GPU memory
- 32GB
- GPU count
- 1
This system provides 32GB per GPU and 32GB in total. The model requires 64GB on one GPU.
sme workstation
Company 64
- Per GPU
- 32GB
- Total GPU memory
- 64GB
- GPU count
- 2
This system provides 32GB per GPU and 64GB in total. The model requires 64GB on one GPU.
sme workstation
Studio 96
- Per GPU
- 96GB
- Total GPU memory
- 96GB
- GPU count
- 1
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the calculated or estimated requirement. Confirm the final precision, software, workload and performance before purchase.
sme workstation
Studio 192
- Per GPU
- 96GB
- Total GPU memory
- 192GB
- GPU count
- 2
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the calculated or estimated requirement. Confirm the final precision, software, workload and performance before purchase.
pcie rack
Value Rack 128
- Per GPU
- 32GB
- Total GPU memory
- 128GB
- GPU count
- 4
This system provides 32GB per GPU and 128GB in total. The model requires 64GB on one GPU.
pcie rack
Value Rack 256
- Per GPU
- 32GB
- Total GPU memory
- 256GB
- GPU count
- 8
This system provides 32GB per GPU and 256GB in total. The model requires 64GB on one GPU.
pcie rack
Enterprise 384
- Per GPU
- 96GB
- Total GPU memory
- 384GB
- GPU count
- 4
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the calculated or estimated requirement. Confirm the final precision, software, workload and performance before purchase.
pcie rack
Enterprise 768
- Per GPU
- 96GB
- Total GPU memory
- 768GB
- GPU count
- 8
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the calculated or estimated requirement. Confirm the final precision, software, workload and performance before purchase.
pcie rack
H200 1.1TB
- Per GPU
- 141GB
- Total GPU memory
- 1,128GB
- GPU count
- 8
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the calculated or estimated requirement. Confirm the final precision, software, workload and performance before purchase.
frontier partner
Frontier Native 2.3TB
- Per GPU
- 288GB
- Total GPU memory
- 2,304GB
- GPU count
- 8
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the calculated or estimated requirement. Confirm the final precision, software, workload and performance before purchase.
frontier partner
Frontier Rack 20TB
- Per GPU
- 288GB
- Total GPU memory
- 20,736GB
- GPU count
- 72
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the calculated or estimated requirement. Confirm the final precision, software, workload and performance before purchase.
Deployment reality
Strengths, limits and runtime route
What it is good at
- Dense 27B capacity for more demanding quality targets.
- Unified text and image input.
- Native 256K context.
- Official support is documented for multiple current serving stacks.
Where to be cautious
- A 64GB minimum leaves little space for long-context cache.
- Extended context and multiple images can make 96GB or more materially more useful.
- Repository weight size does not include every runtime allocation, KV cache, media encoder, batch or concurrent session.
- No GPU Servers benchmark result is claimed until this exact revision has been run under disclosed test conditions.
Serving software
- Transformers
- vLLM
- SGLang
- KTransformers
Before installation
- Use source version fc05daec18b0a78c049392ed2e771dde82bdf654 rather than an unversioned latest branch.
- Start with Transformers only after checking support for the exact architecture and numerical format.
- Use 96GB on one GPU as the procurement starting point; the lower figure is a minimum-memory screen, not a service-level promise.
- Record precision, context, batch, concurrency, container digest, driver and measured latency in the acceptance report.
System requirements
- GPU layout
- The minimum is screened against one GPU. Additional GPUs provide replicas or throughput unless the chosen runtime supports model parallelism.
- Context and cache
- 262,144 tokens native; extensible to 1,010,000. Context length, KV cache, batch and concurrent sessions must be tested together; the architecture limit is not a throughput guarantee.
- System RAM
- Plan system RAM above the 55.563GB repository-weight footprint where model staging or CPU offload is required.
- Storage
- Reserve at least 139GB for the pinned weights, runtime cache and one rollback copy; production datasets and logs are additional.
- Serving software
- First-party material names Transformers, vLLM, SGLang, KTransformers. Pin the serving version and container digest because support for recent architectures can change quickly.
- Representative workload
- Acceptance-test higher-quality multimodal reasoning, coding and document work at the intended quality, context, batch, concurrency and response-time target.
Performance: speed, usable context and concurrency depend on the selected system, software and workload. No benchmark is quoted on this page.
Commercial and legal boundary
Apache License 2.0
Commercial use: permitted
The official model card identifies Apache 2.0 licensing.
Always retain the applicable notices and recheck the live terms for the intended organisation, territory, use and distribution route. Obtain legal advice where required; the official licence governs use.
Read the official licenceTechnical questions
Qwen3.5 27B deployment FAQ
What GPU memory does Qwen3.5 27B need?
Use 64GB on one GPU as the lower memory screen and 96GB on one GPU as the safer starting allowance. The final requirement changes with runtime, context, batch, concurrency and precision.
Which GPU Servers product should I start with for Qwen3.5 27B?
Use the compatibility table to find systems that meet the recommended allowance. A system that only meets the minimum can load the model in principle but may not meet the required context or response time.
Can Qwen3.5 27B be used commercially?
The official model card identifies Apache 2.0 licensing. The linked official licence is authoritative; legal advice may be appropriate for the intended use and distribution route.
What a complete Qwen3.5 27B deployment needs
GPU memory is only one part of the system. Storage, data access, serving software, monitoring and administrator handover also affect a reliable deployment.
