4-bit Autotrain compatible Awq Conversational Endpoints compatible Mixtral Quantized Region:us Safetensors Sharded Tensorflow
Model Card on HF 🤗: https://huggingface.co/meetkai/functionary-medium-v2.4-AWQ
Functionary Medium V2.4 AWQ Benchmarks
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
What is the LLM Explorer Rank (Score)
Functionary Medium V2.4 AWQ Parameters and Internals
| LLM Name | Functionary Medium V2.4 AWQ |
| Repository 🤗 | https://huggingface.co/meetkai/functionary-medium-v2.4-AWQ |
| Model Size | 6.5b |
| Required VRAM | 24.7 GB |
| Updated | 2025-09-23 |
| Maintainer | meetkai |
| Model Type | mixtral |
| Model Files | |
| AWQ Quantization | Yes |
| Quantization Type | awq |
| Model Architecture | MixtralForCausalLM |
| License | mit |
| Context Length | 32768 |
| Model Max Length | 32768 |
| Transformers Version | 4.38.2 |
| Tokenizer Class | LlamaTokenizer |
| Padding Token | </s> |
| Vocabulary Size | 32004 |
| Torch Data Type | float16 |
Best Alternatives to Functionary Medium V2.4 AWQ
Best Alternatives |
Context / RAM |
Downloads |
Likes |
|---|---|---|---|
| Mixtral 8x7B Instruct V0.1 AWQ | 32K / 24.7 GB | 11814 | 58 |
| Dolphin 2.7 Mixtral 8x7b AWQ | 32K / 24.7 GB | 7363 | 23 |
| ...kaLM Mixtral 8x7B V0.2 DPO AWQ | 32K / 24.7 GB | 6 | 0 |
| Mixtral 8x7B Instruct V0.1 AWQ | 32K / 24.7 GB | 6 | 0 |
| Karakuri Lm 8x7b Chat V0.1 AWQ | 32K / 24.7 GB | 5 | 0 |
| Taiwan LLM 8x7B DPO AWQ | 32K / 24.7 GB | 7 | 1 |
| Mixtral Instruct AWQ | 32K / 24.7 GB | 1750 | 43 |
| Mixtral 8x7b V0.1 AWQ | 32K / 24.7 GB | 1241 | 10 |
| H2ogpt Mixtral 8x7b 32K AWQ | 32K / 24.7 GB | 12 | 0 |
| Synatra Mixtral 8x7B AWQ | 32K / 24.7 GB | 6 | 3 |
Note: green Score (e.g. "73.2") means that the model is better than meetkai/functionary-medium-v2.4-AWQ .
Rank the Functionary Medium V2.4 AWQ Capabilities
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124