Will a local LLM run on your hardware? GGUF quant, buy-vs-rent-vs-API cost, used-GPU prices.
Abgeleitet aus den Transporten, die dieser Eintrag deklariert (streamable-http). Ein Client, der hier nicht steht, ist damit nicht ausgeschlossen — Forge kann ihn nur nicht bestätigen.
Die Verifizierung bestätigt die Identität des Publishers (die Inhaberschaft am Repo), nicht die Sicherheit des Codes. Der Sicherheits-Scan deckt bekannte CVEs und verdächtige Installationsskripte ab.
Aus einem echten MCP-Handshake initialize → tools/list gegen den deklarierten Endpunkt gelesen. Es wurde nie ein Tool aufgerufen — tools/list ist der lesende Introspektionsaufruf, den das Protokoll dafür vorsieht. Es spiegelt wider, was der Server in diesem Moment angeboten hat; ein gehosteter Endpunkt ist an keine Version gebunden und kann sich ohne Ankündigung ändern.
https://vettedconsumer.com/mcp9 Tools · 184 mscan_i_run_itWill a given local LLM run on given hardware? Returns fit, the best quant that fits, theoretical tok/s, and real owner-measured tok/s where available.Will a given local LLM run on given hardware? Returns fit, the best quant that fits, theoretical tok/s, and real owner-measured tok/s where available.
| Parameter | Typ | Beschreibung |
|---|---|---|
| model | string | Model name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names. |
| total_b | number | For an unlisted model: total parameters in billions |
| active_b | number | For an unlisted model: active params in billions (= total for dense, less for MoE) |
| mxfp4 | boolean | True if the model ships natively in MXFP4 (e.g. gpt-oss) |
| hardware | string | Hardware name/id, e.g. 'rtx-3090', 'Mac 128GB', 'Strix Halo'. Use list_hardware to see known ones. |
| vram_gb | number | For custom hardware: VRAM or unified memory in GB |
| bandwidth_gbps | number | For custom hardware: memory bandwidth in GB/s |
| unified | boolean | True for unified-memory machines (Macs, Strix Halo, CPU+RAM) |
| context | number | Context window in tokens (default 8192) |
| kv_precision | string | KV cache precision (default f16) |
recommend_quantWhich GGUF quantization to download for a model on given hardware: the full quant ladder with file size, max context, and tok/s for each, plus the recommended pick.Which GGUF quantization to download for a model on given hardware: the full quant ladder with file size, max context, and tok/s for each, plus the recommended pick.
| Parameter | Typ | Beschreibung |
|---|---|---|
| model | string | Model name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names. |
| total_b | number | For an unlisted model: total parameters in billions |
| active_b | number | For an unlisted model: active params in billions (= total for dense, less for MoE) |
| mxfp4 | boolean | True if the model ships natively in MXFP4 (e.g. gpt-oss) |
| hardware | string | Hardware name/id, e.g. 'rtx-3090', 'Mac 128GB', 'Strix Halo'. Use list_hardware to see known ones. |
| vram_gb | number | For custom hardware: VRAM or unified memory in GB |
| bandwidth_gbps | number | For custom hardware: memory bandwidth in GB/s |
| unified | boolean | True for unified-memory machines (Macs, Strix Halo, CPU+RAM) |
| context | number | Context window in tokens (default 8192) |
| kv_precision | string | KV cache precision (default f16) |
cheapest_hardware_for_modelThe cheapest catalogued, buyable machine that runs a given model at Q4 with the requested context.The cheapest catalogued, buyable machine that runs a given model at Q4 with the requested context.
| Parameter | Typ | Beschreibung |
|---|---|---|
| model | string | Model name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names. |
| total_b | number | For an unlisted model: total parameters in billions |
| active_b | number | For an unlisted model: active params in billions (= total for dense, less for MoE) |
| mxfp4 | boolean | True if the model ships natively in MXFP4 (e.g. gpt-oss) |
| context | number | Context window in tokens (default 8192) |
list_modelsList the local LLM model classes the tools know about (params, dense/MoE, native context).List the local LLM model classes the tools know about (params, dense/MoE, native context).
Für dieses Tool wurde kein Eingabeschema veröffentlicht.
list_hardwareList the machines the tools know about (memory, bandwidth, price, buy link).List the machines the tools know about (memory, bandwidth, price, buy link).
Für dieses Tool wurde kein Eingabeschema veröffentlicht.
cost_compareBuy vs rent vs API cost to run a model locally: monthly/1y/3y totals, break-even months, and the energy cost per 1M tokens. Same math as /cost-calculator/.Buy vs rent vs API cost to run a model locally: monthly/1y/3y totals, break-even months, and the energy cost per 1M tokens. Same math as /cost-calculator/.
| Parameter | Typ | Beschreibung |
|---|---|---|
| hardware | string | Catalogued hardware name/id (see list_hardware), e.g. 'rtx-3090-used' |
| price_usd | number | For custom hardware: price in USD |
| tdp_w | number | For custom hardware: board power draw in watts |
| hours | number | Active hours per day (default 3) |
| tokens | number | Tokens generated per day, for the API comparison (default 300000) |
| kwh | number | Electricity $/kWh (default 0.16) |
| rent | number | Cloud GPU $/hour (default 0.59) |
| api | number | API $/million tokens (default 1.0) |
recommend_hardwareRanked list of catalogued, buyable machines that run a model at the requested context, cheapest first, with an optional budget cap.Ranked list of catalogued, buyable machines that run a model at the requested context, cheapest first, with an optional budget cap.
| Parameter | Typ | Beschreibung |
|---|---|---|
| model | string | Model name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names. |
| total_b | number | For an unlisted model: total parameters in billions |
| active_b | number | For an unlisted model: active params in billions (= total for dense, less for MoE) |
| mxfp4 | boolean | True if the model ships natively in MXFP4 (e.g. gpt-oss) |
| context | number | Context window in tokens (default 8192) |
| kv_precision | string | KV cache precision (default f16) |
| budget | number | Optional max price in USD |
get_used_gpu_pricesCurrent typical used-GPU prices for local-AI rigs (eBay Browse API median asking + hand-verified, monthly).Current typical used-GPU prices for local-AI rigs (eBay Browse API median asking + hand-verified, monthly).
| Parameter | Typ | Beschreibung |
|---|---|---|
| gpu | string | Optional name/id filter, e.g. "3090" |
compare_hardwareSide-by-side memory, bandwidth, price, and (with a model) fit + tok/s for 2 to 4 machines.Side-by-side memory, bandwidth, price, and (with a model) fit + tok/s for 2 to 4 machines.
| Parameter | Typ | Beschreibung |
|---|---|---|
| hardware* | string | 2 to 4 hardware names/ids, comma-separated |
| model | string | Model name, e.g. 'Llama 70B', 'gpt-oss-120B', 'Qwen 32B'. Use list_models to see known names. |
| total_b | number | For an unlisted model: total parameters in billions |
| active_b | number | For an unlisted model: active params in billions (= total for dense, less for MoE) |
| mxfp4 | boolean | True if the model ships natively in MXFP4 (e.g. gpt-oss) |
| context | number | Context window in tokens (default 8192) |
| kv_precision | string | KV cache precision (default f16) |
9 von 9 Tools haben eine Beschreibung veröffentlicht.
Tool-Namen und -Beschreibungen stammen vom Publisher und werden wortgetreu als inerter Text angezeigt. Es sind die Zeichenketten, die ein MCP-Client an ein Modell übergibt, deshalb prüft Forge sie auf Prompt-Injection-Muster — jeder Befund erscheint oben beim Sicherheits-Scan. „Privilegiert“ ist ein Schlagwort-Treffer im Tool-Namen, keine Prüfung dessen, was das Tool tut: ein harmlos klingender Name kann trotzdem alles tun.
Will a local LLM run on your hardware? GGUF quant, buy-vs-rent-vs-API cost, used-GPU prices.
Verlinkte Namen öffnen den Forge-Index aller Einträge, bei denen dieses Tool beobachtet wurde. Alle indexierten Tools durchsuchen.
Dieser Eintrag veröffentlicht kein npm-Paket, daher hat Forge keinen Abhängigkeitsbaum dafür. Das ist eine Lücke in der Abdeckung — keine Aussage, dass er keine Abhängigkeiten hat.