Catalog checked on September 11, 2026
The catalog API returned these three entries. Memory, disk and context figures below reproduce its fields. This table records the API response on the review date. The saved source responses preserve the catalog, tier and inventory evidence; check the live API for changes.
| Model ID | Quantization | Required memory | Approximate disk | Maximum context |
|---|---|---|---|---|
| qwen3.8-27b-4bit | 4-bit | 24 GB | 16 GB | 16,384 |
| qwen3.8-27b-8bit | 8-bit | 48 GB | 30 GB | 32,768 |
| qwen3.8-27b-bf16 | BF16 (16-bit) | 96 GB | 55 GB | 32,768 |
The corresponding model repositories are Qwen3.8-27B-4bit, Qwen3.8-27B-8bit and Qwen3.8-27B-bf16. Their public repository metadata was reachable during review. Repository availability does not establish inference quality or rental stock.
Use the catalog ID in the rental API
The short ID, such as qwen3.8-27b-4bit, identifies the platform model. The longer mlx-community/... name identifies the repository used by the serving runtime. Keep those fields separate in your integration. Copy the assigned model ID from the customer dashboard and use the documented rental request.
For a reproducible evaluation, also record the repository revision. A repository name can remain unchanged while its files are updated. The September 11 response includes a 40-character revision hash for each entry. The reviewed agent downloads that revision and serves its local snapshot. Preserve the full hash with evaluation results. The hash identifies the intended model files. This review did not verify a running rental against those files. Pinned download behavior
Preserve the exact model revision
The September 11 catalog contains these revision hashes. Public Hugging Face revision metadata resolved each hash during the review. This checks repository identity and reachability; it does not test generated answers.
| Catalog model | Pinned revision |
|---|---|
| qwen3.8-27b-4bit | 3e6447f082e89cc7f0bc6e5441afd38dfce760ff |
| qwen3.8-27b-8bit | 815b83c0df8ffd1d1b5244cf75fd6ef14fca9ef9 |
| qwen3.8-27b-bf16 | 6f265714824f3c38d4452baa1628aef3d9b9aae9 |
Hugging Face supports selecting a repository snapshot by its full commit hash. Saving the hash helps separate a runtime change from a change in the model files. Download revision documentation
Read the model card associated with the revision for intended uses, training context and evaluation limits. Hugging Face's model-card format includes these fields, but their presence and completeness vary by repository. A conversion repository can require checking the original model card as well. Model card documentation
Keep tokenizer and prompt-format changes in the evaluation record too. The same weight revision can produce different behavior when the application changes its system instructions or generation settings.
Quantization is a choice to evaluate
Lower-bit weights reduce the space used to store model parameters. Whether the resulting model is good enough depends on the task. The quantization comparison guide explains how to evaluate the variants before paying for more memory or accepting a lower-memory configuration.
For extraction, check whether the output contains the requested fields and preserves exact numbers. For code, run the generated code against meaningful checks. For an assistant, include questions where an honest uncertainty response is preferable to a plausible answer. Keep the prompts and scoring rules identical between variants.
Context is also a capacity limit
An advertised maximum context is not an instruction to fill every request to that limit. Your prompt, conversation history and requested answer need an appropriate budget. Longer prompts can take more time before the first token and consume more runtime memory.
Build an input-length check into your application. When a document is too large, choose a deliberate strategy such as selecting relevant passages, shortening history or rejecting the request with a clear explanation. Do not let accidental truncation decide what the model reads.
A catalog entry is not a machine listing
The same review found no machines in the marketplace API. The current tier descriptions also refer to these 27B configurations. The September 11 response no longer includes the older Ultra tier. Arbitrary repositories, private fine-tunes and clustered Macs are outside the supported release described in the customer documentation.
Check both endpoints again when you are ready to rent. Providers can use this table to check memory and disk before following the setup guide. Renters should compare the model evaluation with the 30-day cost.
Sources and references
Reviewed September 11, 2026. Product statements come from public APIs, provider documentation and published application code. Technical references explain the evaluation methods. Authenticated rental and payout behavior has not been tested.
- Compute agent source. PROXIES.SX.
- Model catalog API. PROXIES.SX.
- Marketplace inventory API. PROXIES.SX.
- Download files from the Hub. Hugging Face.
- Model cards. Hugging Face.