MetaMath-Mistral-7B-DFT2-GGUF GGUF download | Hugging Bay

Q: What is this model?

mradermacher/MetaMath-Mistral-7B-DFT2-GGUF is an open-weights language model for general published by mradermacher, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for llm: mradermacher/MetaMath-Mistral-7B-DFT2-GGUF · transformers

Q: Can I use it commercially?

It is released under the apache-2.0 license. Commercial use is allowed. Permissive open license: commercial use, modification, and redistribution are permitted.

Q: How big is it?

mradermacher/MetaMath-Mistral-7B-DFT2-GGUF has 7B parameters. Hosted here: 1 file, 4.37 GB. Full repo upstream: 63.9 GB. The recommended download, MetaMath-Mistral-7B-DFT2.Q4_K_M.gguf (Q4_K_M), is 4.37 GB.

Q: What can I download here?

Hosted here: 1 file, 4.37 GB. Full repo upstream: 63.9 GB. The original release is at https://huggingface.co/mradermacher/MetaMath-Mistral-7B-DFT2-GGUF.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 1 hosted file carries a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-mradermacher-metamath-mistral-7b-dft2-gguf/safety on Hugging Bay.

Q: Will mradermacher/MetaMath-Mistral-7B-DFT2-GGUF run on my computer?

We can’t check the fit; we don’t know your machine. We don’t have your machine’s specs, so no check ran and no verdict is shown. Answer two quick questions and we’ll estimate, from the memory you tell us, whether it fits your machine. Or skip it; you can still download; fit isn’t checked.

mradermacher

MetaMath-Mistral-7B-DFT2-GGUF

mradermacher/MetaMath-Mistral-7B-DFT2-GGUF

generalLicense: apache-2.0Hashes recordedGGUF

Content controls: not assessed.

Model from Hugging Face for llm: mradermacher/MetaMath-Mistral-7B-DFT2-GGUF · transformers

View as JSON →

1 hosted of 14 listed

Hashes recorded. Date not recorded.

File	Größe	SHA-256	Quelle	Herunterladen
Weights
`MetaMath-Mistral-7B-DFT2.Q4_K_M.gguf` Default	4.37 GB	`3a144f25…29d28301` `3a144f25ec30aed52f286afc60caff398d0929e297a2ab04694c89fe29d28301`	Hosted	Herunterladen
`MetaMath-Mistral-7B-DFT2.IQ4_XS.gguf`	3.94 GB	`80f6e483…ed70ff1b` `80f6e483bc05eae7fda71be86dae113b4bd0e83d21dca684d7e89ed3ed70ff1b`	Upstream only	File metadata
`MetaMath-Mistral-7B-DFT2.Q2_K.gguf`	2.72 GB	`8485121f…d7305abb` `8485121f163062a36a0991097c04e684871b52fa77590eccbebcfe89d7305abb`	Upstream only	File metadata
`MetaMath-Mistral-7B-DFT2.Q3_K_L.gguf`	3.82 GB	`4c1ce277…6eb3bb69` `4c1ce277b36cd0dc591916570a0537a763e27a2335f948348e8a03a36eb3bb69`	Upstream only	File metadata
`MetaMath-Mistral-7B-DFT2.Q3_K_M.gguf`	3.52 GB	`5b4d9fc7…b27b4e21` `5b4d9fc7c79f0c45a0f61c21b6e88bde31426693333e6ac088784076b27b4e21`	Upstream only	File metadata
`MetaMath-Mistral-7B-DFT2.Q3_K_S.gguf`	3.16 GB	`482b61c7…047d1166` `482b61c7e5fffbec4f468e761a93716ba81e073bb6a03e5abca2a104047d1166`	Upstream only	File metadata
`MetaMath-Mistral-7B-DFT2.Q4_K_S.gguf`	4.14 GB	`cdc01d8d…a10c9b7d` `cdc01d8da4b5c85ff9f82eb7e2351f397e7f0b121a1a8704e248b6d1a10c9b7d`	Upstream only	File metadata
`MetaMath-Mistral-7B-DFT2.Q5_K_M.gguf`	5.13 GB	`98945be1…a234a579` `98945be1f127c4cc2b9593bb7ac65b6507339c579cc98f4aa6340956a234a579`	Upstream only	File metadata
`MetaMath-Mistral-7B-DFT2.Q5_K_S.gguf`	5 GB	`8b490502…d123fdb0` `8b490502db1054a2d6b358eb829dac6a6c4d12a78856cc9e1f1fd45ad123fdb0`	Upstream only	File metadata
`MetaMath-Mistral-7B-DFT2.Q6_K.gguf`	5.94 GB	`91542685…468208cb` `9154268590d433f0b75947efeaf8f1033246411911efb0b6db2299fe468208cb`	Upstream only	File metadata
`MetaMath-Mistral-7B-DFT2.Q8_0.gguf`	7.7 GB	`639bef0c…0e602f46` `639bef0cb0c7418be506ae40b735d5e500c033aa2cec20f45ecaa2460e602f46`	Upstream only	File metadata
`MetaMath-Mistral-7B-DFT2.f16.gguf`	14.5 GB	`ce064080…8cf6477e` `ce0640808cba237be6236b6b833c83ae14519adf721ca21ac2a7f5d58cf6477e`	Upstream only	File metadata
Docs
`.gitattributes`	2.39 KB	—	Upstream only	File metadata
`README.md`	3.64 KB	—	Upstream only	File metadata

Einen Download prüfen

In the folder where you saved MetaMath-Mistral-7B-DFT2.Q4_K_M.gguf, run:

macOS

shasum -a 256 -- 'MetaMath-Mistral-7B-DFT2.Q4_K_M.gguf'

Linux

sha256sum -- 'MetaMath-Mistral-7B-DFT2.Q4_K_M.gguf'

Windows

Get-FileHash -LiteralPath 'MetaMath-Mistral-7B-DFT2.Q4_K_M.gguf' -Algorithm SHA256

Compare the result with the recorded SHA-256.

MetaMath-Mistral-7B-DFT2-GGUF

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