Fara1.5-27B vs Mage-VL-Cowork

Fara1.5-27B 65

Model card 20, Intended use, out-of-scope use and known limitations, the architecture, the parameters, the context, the language (English only) and the data cut-off (20 March 2026) are all on the card. Training data 15, A data section that names the kinds of source and the mix, the scale, the cut-off (last acquisition 20 March 2026) and the filtering (a verifier keeps only successful trajectories). Last change 10, the last commit, on 27 July 2026, is 106 days before this check and within 180. Responsiveness 5, Of the 5 discussions that aren't pull requests (22 to 29 July 2026), 1 has a reply from a microsoft member, which is a few, counted on 10 November by author flags and dates with a script, text not read. Version policy 5, the card says future updates will ship as separately versioned models with their own cards, and the earlier Fara model stays in its own repository. File health 10, Config, template and card agree on the architecture and the 262,144-token context. 20 + 15 + 10 + 5 + 5 + 10 = 65.

Mage-VL-Cowork 54

The card covers intended use, architecture, parameters, context and language, and misses limitations and a cut-off (14). Training data is described with named sets and sizes but no cut-off (5). The files are four days old (20). Two questions opened on 31 October have no Microsoft reply (0). It's a first release (5), and the files agree with the card (10).

Fara1.5-27B 75

File safety 25, safetensors only, no .bin, .pt or .pth files and no Python in the repository. Provenance 15, the files sit in Microsoft's verified microsoft organisation, which the card's GitHub repository belongs to (10), and the Hub gives a SHA-256 for the large files (5). Safety evaluation 0, the card says the model was red-teamed on Azure for groundedness, jailbreak resistance, harmful content and copyright, and publishes no results. Agent guidance 10, the card says what the trained pauses and refusals cover (three kinds of critical point, with the actions it stops on, and refusal data for harmful tasks) and the safeguards to add: a sandbox with no host files or credentials, allow-listed browsing, live monitoring with a way to halt, and checking its output. Licence risk 15, MIT has no use policy, threshold or change clause. Security programme 10, the microsoft/fara repository has a SECURITY.md, Microsoft's standard route to MSRC (5), and MSRC publishes advisories in public, as recorded on our other Microsoft listings (5). 25 + 15 + 0 + 10 + 15 + 10 = 75.

Mage-VL-Cowork 65

File safety gets 15, safetensors only but loaded with trust_remote_code. Provenance gets 15 for files in Microsoft's organisation with a hash for every file. Licence risk keeps 15 under Apache 2.0. The security programme gets 10 for the repository's SECURITY.md route to MSRC and MSRC's public advisories. Agent guidance gets 10 for a statement that it runs arbitrary commands and a list of safeguards (sandbox, human confirmation, no credentials, allow-listing against injection), with nothing on trained refusals. Safety evaluation scores 0, as none is published.

Fara1.5-27B 55

Memory 10, the only build from Microsoft is the BF16 safetensors, 54.71 GB, and 54.71 GB × 1.2 = 65.7 GB, which fits the reference machine but not 64 GB. bartowski's GGUF isn't read for this line. Runtimes 15, the architecture is Qwen3_5ForConditionalGeneration, which vLLM 0.33.0, SGLang 0.5.23 and Transformers 5.22.2 run from the safetensors files, three at 5 each. Builds 0, Microsoft publishes the BF16 weights only. Terms 15, MIT in the card's metadata and its licence section, an OSI licence with nothing added. Download 10, the Hub API reports gated false on 10 November 2026, so the files download with no account and nothing to accept. Hosted 5, the card links an Azure Foundry page for this model, Microsoft's own platform, and Featherless is live for it on Hugging Face. 10 + 15 + 0 + 15 + 10 + 5 = 55.

Mage-VL-Cowork 60

Memory earns the full 30, since the only build is 9.50 GB of BF16 files that need about 11.4 GB with the fifth added. Runtimes get 5 for vLLM, whose released code (0.33.0) carries the LLaVA-OneVision-2 architecture this model's config names, though Microsoft doesn't document it. Transformers runs it only through Microsoft's remote code, SGLang only in Microsoft's own container, and llama.cpp has nothing for it. Builds score 0, with no quantised build from Microsoft. Terms get 15 for Apache 2.0 with nothing added, the base models' licences included. Download gets 10 for an ungated repository, and hosted too 0, with no inference provider mapped.

Fara1.5-27B 80

Chat template 20, chat_template.jinja in the repository (7,756 characters), Qwen 3.5's template. Tool-calling format 25, Microsoft documents the format: a tool_call block holding a JSON call to computer_use, a table of the supported actions, the system prompt to send, a serve command for vLLM and a worked loop, with the full schema in its harness. Trained tool calling 10, one action per step: the model sees a screenshot, emits one tool call, and waits for the next screenshot, the one-at-a-time band. Structured output 15, Read for a computer-use model as typed outputs, as the other one we list was read. Reasoning control 0, the card says each reply opens with a chain-of-thought block and documents no way to turn it off or budget it. Context 10, 262,144 tokens per the card's details table, and config.json gives the language model 262,144 positions. 20 + 25 + 10 + 15 + 0 + 10 = 80.

Mage-VL-Cowork 85

Read for a computer-use model, the tool-calling, trained tool calling and structured-output lines stand for what it takes and returns. Microsoft gives the system prompt and both tool schemas verbatim, what comes back for each channel, the SGLang parser and its own parsing code (25). It was trained to emit up to 15 calls of one kind per reply (20). Each action is JSON against a documented schema (15). The chat template is in the repository (20). Reasoning control scores 0, as turning thinking off isn't documented, and context 5 for a 32,768-token trained window.