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Compare hardware

compare_hardware

Side-by-side memory, bandwidth, price, and (with a model) fit + tok/s for 2 to 4 machines.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoModel name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names.
mxfp4NoTrue if the model ships natively in MXFP4 (e.g. gpt-oss)
contextNoContext window in tokens (default 8192)
total_bNoFor an unlisted model: total parameters in billions
active_bNoFor an unlisted model: active params in billions (= total for dense, less for MoE)
hardwareYes2 to 4 hardware names/ids, comma-separated
kv_precisionNoKV cache precision (default f16)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It lists what is compared (memory, bandwidth, price, etc.) but does not mention side effects, mutability, or data sources. For a read-only comparison tool, this is acceptable but not enriched beyond the core behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that conveys the tool's purpose and scope efficiently with no redundant information. Every element (side-by-side, specific metrics, machine count) is directly relevant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 7 parameters, no output schema, and 8 sibling tools, the description is relatively sparse. It does not clarify what 'fit' means, how to use the optional model-related parameters, or the output format. The schema descriptions partially compensate, but the description could be more helpful.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description hints that the 'model' parameter enables fit and tok/s calculation but adds no new meaning beyond the schema's parameter descriptions. It does not elaborate on how parameters interact or their formats.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states side-by-side comparison of specific hardware attributes: memory, bandwidth, price, and with a model also fit and tokens/second. It specifies the tool handles 2 to 4 machines, distinguishing it from sibling tools like 'cost_compare' which focuses only on price.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for comparing multiple hardware options but does not explicitly state when to use this tool versus siblings like 'cheapest_hardware_for_model', 'recommend_hardware', or 'can_i_run_it'. No exclusion or alternative guidance is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.7/5.0
Disambiguation4/5

Tools have mostly distinct purposes, though there is some overlap between cheapest_hardware_for_model and recommend_hardware, which both suggest machines for a model. Can_i_run_it also partially overlaps with these. However, descriptions clearly differentiate them.

Naming Consistency3/5

Most tools follow verb_noun pattern (list_hardware, compare_hardware), but can_i_run_it is a question and cost_compare is noun_verb, creating minor inconsistency.

Tool Count5/5

9 tools is well-scoped for a domain of hardware/model comparison, covering all key actions without being excessive.

Completeness4/5

Covers main workflows: compatibility check, cost analysis, recommendations, and listings. Lacks advanced filtering or detailed hardware specs, but core functionality is present.

Resources