Compatibility Matrix

This page lists what the current Tensormesh release supports: the models it serves, the serving engines it runs in front of, the cache and storage features it provides, and the failures it recovers from — along with the exact versions to deploy. Tensormesh is released and supported as a single matched set, so the versions below are the ones to run together.

Tensormesh is released as a matched set. Deploy a single row’s versions together — the cache engine, operator, and Helm chart are supported as a unit.

Cache engine	Operator	Helm chart	Serving image	Status	As of
`v0.4.5`	`v0.1.2`	`0.4.5`	`lmcache/vllm-openai:v0.4.5`	✅ Supported	2026-05-27
`v0.5.0`	`nightly-20260508-c7394b8`	`0.4.5`	`lmcache/vllm-openai:v0.5.0`	🚧 Upgrade in validation	2026-06-24

Current as of 2026-06-24.

Deploy these versions together and pin them explicitly — never latest. Mixing versions across the cache engine, operator, and chart is not supported.

What’s supported

Supported models

Models supported on the current Tensormesh release.

Model	Hugging Face ID	Status
DeepSeek-R1-Distill 1.5B	`deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B`	✅ Supported
GLM-4 9B	`THUDM/glm-4-9b`	✅ Supported
Llama 3.2 1B	`meta-llama/Llama-3.2-1B`	✅ Supported
Qwen3 0.6B	`Qwen/Qwen3-0.6B`	✅ Supported

On the roadmap: Llama 3.1 8B, MiniMax.

Serving engines

Serving engines supported in front of the Tensormesh cache.

Serving engine	Notes	Status
vLLM	Bundled in the serving image	✅ Supported

On the roadmap: NVIDIA Dynamo, SGLang, TensorRT-LLM, vLLM via stack-operator.

Cache features & storage

Cache and storage capabilities available on the current release.

Capability	Type	Status
L2 filesystem offload (fs_native)	Filesystem	✅ Supported

On the roadmap: GPUDirect Storage (GDS), Peer-to-peer KV transfer.

Resilience

Failures Tensormesh detects and recovers from automatically.

Scenario	Status
Cache engine pod failure recovery	⚠️ Known issue

On the roadmap: Network partition recovery, Operator pod failure recovery.

Performance

Performance characteristics of the current release.

Benchmark	Hardware	Status
L1 cache-hit speedup (Qwen3 0.6B)	H200	✅ Supported

How to read this

✅ Supported — works on the current release.
⚠️ Known issue — a problem we’re aware of and actively tracking on the current release.
On the roadmap — planned, not yet available. Absence from this page doesn’t mean something can’t work, only that it isn’t supported yet.

Always deploy the versions in Supported versions above as a set, and pin them explicitly rather than using latest. If you need to attach an existing vLLM workload to Tensormesh, see Modify an Existing Deployment.