#7618·textgen

unknown model architecture: 'minimax-m3'

Author: B0rnerCreated Jul 10, 2026Updated Jul 10, 2026
Labelsbug

Describe the bug

If I load MiniMax M3 MXFP4 Version I get the error: unknown model architecture: 'minimax-m3'

I use the current version on linux, pop os.

Is there an existing issue for this?

  • I have searched the existing issues

Reproduction

Screenshot

No response

Logs

INFO     Loading "MiniMax-M3-MXFP4_MOE-00001-of-00007.gguf"     
 INFO     Using gpu_layers=auto | ctx_size=auto | cache_type=fp16
ggml_cuda_init: found 2 CUDA devices (Total VRAM: 129357 MiB):
  Device 0: NVIDIA RTX PRO 6000 Blackwell Workstation Edition, compute capability 12.0, VMM: yes, VRAM: 97249 MiB
  Device 1: NVIDIA GeForce RTX 5090, compute capability 12.0, VMM: yes, VRAM: 32107 MiB
load_backend: loaded CUDA backend from /home/app/textgen/installer_files/env/lib/python3.13/site-packages/llama_cpp_binaries/bin/libggml-cuda.so
load_backend: loaded RPC backend from /home/app/textgen/installer_files/env/lib/python3.13/site-packages/llama_cpp_binaries/bin/libggml-rpc.so
load_backend: loaded CPU backend from /home/app/textgen/installer_files/env/lib/python3.13/site-packages/llama_cpp_binaries/bin/libggml-cpu-zen4.so
build_info: b1-8e15485
system_info: n_threads = 24 (n_threads_batch = 24) / 48 | CUDA : ARCHS = 500,610,700,750,800,860,890 | USE_GRAPHS = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | BMI2 = 1 | AVX512 = 1 | AVX512_VBMI = 1 | AVX512_VNNI = 1 | AVX512_BF16 = 1 | LLAMAFILE = 1 | OPENMP = 1 | REPACK = 1 | 
Running without SSL
init: using 47 threads for HTTP server
Web UI is disabled
start: binding port with default address family
main: loading model
common_init_result: fitting params to device memory, for bugs during this step try to reproduce them with -fit off, or provide --verbose logs if the bug only occurs with -fit on
common_params_fit_impl: getting device memory data for initial parameters:
llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'minimax-m3'
llama_model_load_from_file_impl: failed to load model
common_fit_params: encountered an error while trying to fit params to free device memory: failed to load model
common_fit_params: fitting params to free memory took 0.23 seconds
llama_model_load_from_file_impl: using device CUDA0 (NVIDIA RTX PRO 6000 Blackwell Workstation Edition) (0000:11:00.0) - 96676 MiB free
llama_model_load_from_file_impl: using device CUDA1 (NVIDIA GeForce RTX 5090) (0000:e1:00.0) - 30003 MiB free
llama_model_loader: additional 6 GGUFs metadata loaded.
llama_model_loader: loaded meta data with 49 key-value pairs and 948 tensors from user_data/models/MiniMax-M3-MXFP4_MOE-00001-of-00007.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = minimax-m3
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Minimax-M3
llama_model_loader: - kv   3:                           general.basename str              = Minimax-M3
llama_model_loader: - kv   4:                       general.quantized_by str              = Unsloth
llama_model_loader: - kv   5:                         general.size_label str              = 128x16B
llama_model_loader: - kv   6:                            general.license str              = other
llama_model_loader: - kv   7:                       general.license.name str              = minimax-community
llama_model_loader: - kv   8:                       general.license.link str              = LICENSE
llama_model_loader: - kv   9:                           general.repo_url str              = https://huggingface.co/unsloth
llama_model_loader: - kv  10:                               general.tags arr[str,6]       = ["multimodal", "moe", "agent", "codin...
llama_model_loader: - kv  11:                     minimax-m3.block_count u32              = 60
llama_model_loader: - kv  12:                  minimax-m3.context_length u32              = 1048576
llama_model_loader: - kv  13:                minimax-m3.embedding_length u32              = 6144
llama_model_loader: - kv  14:             minimax-m3.feed_forward_length u32              = 12288
llama_model_loader: - kv  15:            minimax-m3.attention.head_count u32              = 64
llama_model_loader: - kv  16:         minimax-m3.attention.head_count_kv u32              = 4
llama_model_loader: - kv  17:                  minimax-m3.rope.freq_base f32              = 5000000.000000
llama_model_loader: - kv  18: minimax-m3.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  19:                    minimax-m3.expert_count u32              = 128
llama_model_loader: - kv  20:               minimax-m3.expert_used_count u32              = 4
llama_model_loader: - kv  21:              minimax-m3.expert_gating_func u32              = 2
llama_model_loader: - kv  22:            minimax-m3.attention.key_length u32              = 128
llama_model_loader: - kv  23:          minimax-m3.attention.value_length u32              = 128
llama_model_loader: - kv  24:      minimax-m3.expert_feed_forward_length u32              = 3072
llama_model_loader: - kv  25:            minimax-m3.rope.dimension_count u32              = 64
llama_model_loader: - kv  26:             minimax-m3.expert_shared_count u32              = 1
llama_model_loader: - kv  27:            minimax-m3.expert_weights_scale f32              = 2.000000
llama_model_loader: - kv  28:             minimax-m3.expert_weights_norm bool             = true
llama_model_loader: - kv  29:       minimax-m3.leading_dense_block_count u32              = 3
llama_model_loader: - kv  30:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  31:                         tokenizer.ggml.pre str              = minimax-m2
llama_model_loader: - kv  32:                      tokenizer.ggml.tokens arr[str,200064]  = ["Ā", "ā", "Ă", "ă", "Ą", "ą", ...
llama_model_loader: - kv  33:                  tokenizer.ggml.token_type arr[i32,200064]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  34:                      tokenizer.ggml.merges arr[str,199744]  = ["Ġ Ġ", "Ġ t", "Ġ a", "i n", "e r...
llama_model_loader: - kv  35:                tokenizer.ggml.bos_token_id u32              = 200019
llama_model_loader: - kv  36:                tokenizer.ggml.eos_token_id u32              = 200020
llama_model_loader: - kv  37:            tokenizer.ggml.unknown_token_id u32              = 16474
llama_model_loader: - kv  38:            tokenizer.ggml.padding_token_id u32              = 200000
llama_model_loader: - kv  39:                    tokenizer.chat_template str              = {# ---------- special token variables...
llama_model_loader: - kv  40:               general.quantization_version u32              = 2
llama_model_loader: - kv  41:                          general.file_type u32              = 38
llama_model_loader: - kv  42:                      quantize.imatrix.file str              = MiniMax-M3-GGUF/imatrix_unsloth.gguf
llama_model_loader: - kv  43:                   quantize.imatrix.dataset str              = unsloth_calibration_MiniMax-M3.txt
llama_model_loader: - kv  44:             quantize.imatrix.entries_count u32              = 648
llama_model_loader: - kv  45:              quantize.imatrix.chunks_count u32              = 182
llama_model_loader: - kv  46:                                   split.no u16              = 0
llama_model_loader: - kv  47:                        split.tensors.count i32              = 948
llama_model_loader: - kv  48:                                split.count u16              = 7
llama_model_loader: - type  f32:  355 tensors
llama_model_loader: - type q8_0:  422 tensors
llama_model_loader: - type q5_K:   56 tensors
llama_model_loader: - type q6_K:    3 tensors
llama_model_loader: - type mxfp4:  112 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = MXFP4 MoE
print_info: file size   = 238.86 GiB (4.82 BPW) 
llama_model_load: error loading model: error loading model architecture: unknown model architecture: 'minimax-m3'
llama_model_load_from_file_impl: failed to load model
common_init_from_params: failed to load model 'user_data/models/MiniMax-M3-MXFP4_MOE-00001-of-00007.gguf'
main: exiting due to model loading error

System Info

using a Linux (pop!os) with an AMD Threadripper, 192 GB RAM, RTX Pro 6000, RTX 5090 - both on current driver with CUDA 13.2