$ llama-completion -ngl 0 -fit off -m unsloth_Nemotron-3-Nano-30B-A3B-GGUF_Nemotron-3-Nano-30B-A3B-Q2_K_L.gguf
ggml_cuda_init: found 1 ROCm devices (Total VRAM: 122880 MiB):
Device 0: Radeon 8060S Graphics, gfx1151 (0x1151), VMM: no, Wave Size: 32, VRAM: 122880 MiB (122871 MiB free)
ggml_vulkan: Found 1 Vulkan devices:
ggml_vulkan: 0 = Radeon 8060S Graphics (RADV STRIX_HALO) (radv) | uma: 1 | fp16: 1 | bf16: 0 | warp size: 64 | shared memory: 65536 | int dot: 1 | matrix cores: KHR_coopmat
build: 8351 (77efcba) with GNU 15.2.1 for Linux x86_64
main: llama backend init
main: load the model and apply lora adapter, if any
llama_model_load_from_file_impl: using device ROCm0 (Radeon 8060S Graphics) (0000:c2:00.0) - 122581 MiB free
llama_model_loader: loaded meta data with 53 key-value pairs and 401 tensors from unsloth_Nemotron-3-Nano-30B-A3B-GGUF_Nemotron-3-Nano-30B-A3B-Q2_K_L.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 = nemotron_h_moe
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.sampling.top_p f32 = 1.000000
llama_model_loader: - kv 3: general.sampling.temp f32 = 1.000000
llama_model_loader: - kv 4: general.name str = Nemotron-3-Nano-30B-A3B
llama_model_loader: - kv 5: general.basename str = Nemotron-3-Nano-30B-A3B
llama_model_loader: - kv 6: general.quantized_by str = Unsloth
llama_model_loader: - kv 7: general.size_label str = 30B-A3B
llama_model_loader: - kv 8: general.repo_url str = https://huggingface.co/unsloth
llama_model_loader: - kv 9: nemotron_h_moe.block_count u32 = 52
llama_model_loader: - kv 10: nemotron_h_moe.context_length u32 = 1048576
llama_model_loader: - kv 11: nemotron_h_moe.embedding_length u32 = 2688
llama_model_loader: - kv 12: nemotron_h_moe.feed_forward_length arr[i32,52] = [0, 1856, 0, 1856, 0, 0, 1856, 0, 185...
llama_model_loader: - kv 13: nemotron_h_moe.attention.head_count u32 = 32
llama_model_loader: - kv 14: nemotron_h_moe.attention.head_count_kv arr[i32,52] = [0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, ...
llama_model_loader: - kv 15: nemotron_h_moe.rope.freq_base f32 = 10000.000000
llama_model_loader: - kv 16: nemotron_h_moe.attention.layer_norm_rms_epsilon f32 = 0.000010
llama_model_loader: - kv 17: nemotron_h_moe.attention.layer_norm_epsilon f32 = 0.000010
llama_model_loader: - kv 18: nemotron_h_moe.expert_used_count u32 = 6
llama_model_loader: - kv 19: nemotron_h_moe.expert_group_count u32 = 1
llama_model_loader: - kv 20: nemotron_h_moe.expert_group_used_count u32 = 1
llama_model_loader: - kv 21: nemotron_h_moe.vocab_size u32 = 131072
llama_model_loader: - kv 22: nemotron_h_moe.rope.dimension_count u32 = 84
llama_model_loader: - kv 23: nemotron_h_moe.ssm.conv_kernel u32 = 4
llama_model_loader: - kv 24: nemotron_h_moe.ssm.state_size u32 = 128
llama_model_loader: - kv 25: nemotron_h_moe.ssm.group_count u32 = 8
llama_model_loader: - kv 26: nemotron_h_moe.ssm.inner_size u32 = 4096
llama_model_loader: - kv 27: nemotron_h_moe.ssm.time_step_rank u32 = 64
llama_model_loader: - kv 28: nemotron_h_moe.rope.scaling.finetuned bool = false
llama_model_loader: - kv 29: nemotron_h_moe.attention.key_length u32 = 128
llama_model_loader: - kv 30: nemotron_h_moe.attention.value_length u32 = 128
llama_model_loader: - kv 31: nemotron_h_moe.expert_feed_forward_length u32 = 1856
llama_model_loader: - kv 32: nemotron_h_moe.expert_shared_feed_forward_length u32 = 3712
llama_model_loader: - kv 33: nemotron_h_moe.expert_count u32 = 128
llama_model_loader: - kv 34: nemotron_h_moe.expert_shared_count u32 = 1
llama_model_loader: - kv 35: nemotron_h_moe.expert_weights_norm bool = true
llama_model_loader: - kv 36: nemotron_h_moe.expert_weights_scale f32 = 2.500000
llama_model_loader: - kv 37: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 38: tokenizer.ggml.pre str = pixtral
llama_model_loader: - kv 39: tokenizer.ggml.tokens arr[str,131072] = ["<unk>", "<s>", "</s>", "[INST]", "[...
llama_model_loader: - kv 40: tokenizer.ggml.token_type arr[i32,131072] = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ...
llama_model_loader: - kv 41: tokenizer.ggml.merges arr[str,269443] = ["Ä Ä ", "Ä t", "e r", "i n", "Ä Ä...
llama_model_loader: - kv 42: tokenizer.ggml.bos_token_id u32 = 1
llama_model_loader: - kv 43: tokenizer.ggml.eos_token_id u32 = 11
llama_model_loader: - kv 44: tokenizer.ggml.unknown_token_id u32 = 0
llama_model_loader: - kv 45: tokenizer.ggml.padding_token_id u32 = 999
llama_model_loader: - kv 46: tokenizer.chat_template str = {# Unsloth template fixes #}\n{% macro...
llama_model_loader: - kv 47: general.quantization_version u32 = 2
llama_model_loader: - kv 48: general.file_type u32 = 10
llama_model_loader: - kv 49: quantize.imatrix.file str = Nemotron-3-Nano-30B-A3B-GGUF/imatrix_...
llama_model_loader: - kv 50: quantize.imatrix.dataset str = unsloth_calibration_Nemotron-3-Nano-3...
llama_model_loader: - kv 51: quantize.imatrix.entries_count u32 = 185
llama_model_loader: - kv 52: quantize.imatrix.chunks_count u32 = 80
llama_model_loader: - type f32: 237 tensors
llama_model_loader: - type q5_0: 24 tensors
llama_model_loader: - type q8_0: 24 tensors
llama_model_loader: - type q2_K: 23 tensors
llama_model_loader: - type q3_K: 6 tensors
llama_model_loader: - type iq4_nl: 87 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q2_K - Medium
print_info: file size = 16.85 GiB (4.58 BPW)
load: 0 unused tokens
load: printing all EOG tokens:
load: - 2 ('</s>')
load: - 11 ('<|im_end|>')
load: special tokens cache size = 1000
load: token to piece cache size = 0.8499 MB
print_info: arch = nemotron_h_moe
print_info: vocab_only = 0
print_info: no_alloc = 0
print_info: n_ctx_train = 1048576
print_info: n_embd = 2688
print_info: n_embd_inp = 2688
print_info: n_layer = 52
print_info: n_head = 32
print_info: n_head_kv = [0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0]
print_info: n_rot = 84
print_info: n_swa = 0
print_info: is_swa_any = 0
print_info: n_embd_head_k = 128
print_info: n_embd_head_v = 128
print_info: n_gqa = [0, 0, 0, 0, 0, 16, 0, 0, 0, 0, 0, 0, 16, 0, 0, 0, 0, 0, 0, 16, 0, 0, 0, 0, 0, 0, 16, 0, 0, 0, 0, 0, 0, 16, 0, 0, 0, 0, 0, 0, 0, 0, 16, 0, 0, 0, 0, 0, 0, 0, 0, 0]
print_info: n_embd_k_gqa = [0, 0, 0, 0, 0, 256, 0, 0, 0, 0, 0, 0, 256, 0, 0, 0, 0, 0, 0, 256, 0, 0, 0, 0, 0, 0, 256, 0, 0, 0, 0, 0, 0, 256, 0, 0, 0, 0, 0, 0, 0, 0, 256, 0, 0, 0, 0, 0, 0, 0, 0, 0]
print_info: n_embd_v_gqa = [0, 0, 0, 0, 0, 256, 0, 0, 0, 0, 0, 0, 256, 0, 0, 0, 0, 0, 0, 256, 0, 0, 0, 0, 0, 0, 256, 0, 0, 0, 0, 0, 0, 256, 0, 0, 0, 0, 0, 0, 0, 0, 256, 0, 0, 0, 0, 0, 0, 0, 0, 0]
print_info: f_norm_eps = 0.0e+00
print_info: f_norm_rms_eps = 1.0e-05
print_info: f_clamp_kqv = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale = 0.0e+00
print_info: f_attn_scale = 0.0e+00
print_info: n_ff = [0, 1856, 0, 1856, 0, 0, 1856, 0, 1856, 0, 1856, 0, 0, 1856, 0, 1856, 0, 1856, 0, 0, 1856, 0, 1856, 0, 1856, 0, 0, 1856, 0, 1856, 0, 1856, 0, 0, 1856, 0, 1856, 0, 1856, 0, 1856, 0, 0, 1856, 0, 1856, 0, 1856, 0, 1856, 0, 1856]
print_info: n_expert = 128
print_info: n_expert_used = 6
print_info: n_expert_groups = 1
print_info: n_group_used = 1
print_info: causal attn = 1
print_info: pooling type = 0
print_info: rope type = -1
print_info: rope scaling = linear
print_info: freq_base_train = 10000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn = 1048576
print_info: rope_yarn_log_mul = 0.0000
print_info: rope_finetuned = unknown
print_info: ssm_d_conv = 4
print_info: ssm_d_inner = 4096
print_info: ssm_d_state = 128
print_info: ssm_dt_rank = 64
print_info: ssm_n_group = 8
print_info: ssm_dt_b_c_rms = 0
print_info: model type = 31B.A3.5B
print_info: model params = 31.58 B
print_info: general.name = Nemotron-3-Nano-30B-A3B
print_info: f_embedding_scale = 0.000000
print_info: f_residual_scale = 0.000000
print_info: f_attention_scale = 0.000000
print_info: n_ff_shexp = 3712
print_info: vocab type = BPE
print_info: n_vocab = 131072
print_info: n_merges = 269443
print_info: BOS token = 1 '<s>'
print_info: EOS token = 11 '<|im_end|>'
print_info: EOT token = 11 '<|im_end|>'
print_info: UNK token = 0 '<unk>'
print_info: PAD token = 999 '<SPECIAL_999>'
print_info: LF token = 1010 '�'
print_info: EOG token = 2 '</s>'
print_info: EOG token = 11 '<|im_end|>'
print_info: max token length = 150
load_tensors: loading model tensors, this can take a while... (mmap = true, direct_io = false)
load_tensors: offloading 0 repeating layers to GPU
load_tensors: offloaded 0/53 layers to GPU
load_tensors: CPU_Mapped model buffer size = 17250.60 MiB
.....................................................
common_init_result: added </s> logit bias = -inf
common_init_result: added <|im_end|> logit bias = -inf
llama_context: constructing llama_context
llama_context: n_seq_max = 1
llama_context: n_ctx = 1048576
llama_context: n_ctx_seq = 1048576
llama_context: n_batch = 2048
llama_context: n_ubatch = 512
llama_context: causal_attn = 1
llama_context: flash_attn = auto
llama_context: kv_unified = false
llama_context: freq_base = 10000.0
llama_context: freq_scale = 1
llama_context: CPU output buffer size = 0.50 MiB
llama_kv_cache: CPU KV buffer size = 6144.00 MiB
llama_kv_cache: size = 6144.00 MiB (1048576 cells, 6 layers, 1/1 seqs), K (f16): 3072.00 MiB, V (f16): 3072.00 MiB
llama_memory_recurrent: CPU RS buffer size = 47.62 MiB
llama_memory_recurrent: size = 47.62 MiB ( 1 cells, 52 layers, 1 seqs), R (f32): 1.62 MiB, S (f32): 46.00 MiB
sched_reserve: reserving ...
/home/caleb/Downloads/llama.cpp-aio/src/llama.cpp/src/models/mamba-base.cpp:173: GGML_ASSERT(d_inner % (n_group*n_embd) == 0) failed
[New LWP 45138]
[New LWP 45136]
[New LWP 45135]
[New LWP 45133]
[New LWP 45132]
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Using host libthread_db library "/usr/lib/libthread_db.so.1".
0x00007f27934b2422 in ?? () from /usr/lib/libc.so.6
#0 0x00007f27934b2422 in ?? () from /usr/lib/libc.so.6
#1 0x00007f27934a5edf in ?? () from /usr/lib/libc.so.6
#2 0x00007f2793527fab in wait4 () from /usr/lib/libc.so.6
#3 0x00007f27945633ef in ggml_print_backtrace () from /usr/lib/libggml-base.so.0
#4 0x00007f27945635c3 in ggml_abort () from /usr/lib/libggml-base.so.0
#5 0x00007f279483e03d in llm_build_mamba_base::build_mamba2_layer(llm_graph_input_rs*, ggml_tensor*, llama_model const&, llama_ubatch const&, int) const () from /usr/lib/libllama.so.0
#6 0x00007f279484dcee in llm_build_nemotron_h::llm_build_nemotron_h(llama_model const&, llm_graph_params const&) () from /usr/lib/libllama.so.0
#7 0x00007f27947accfd in llama_model::build_graph(llm_graph_params const&) const () from /usr/lib/libllama.so.0
#8 0x00007f27946c2b45 in llama_context::graph_reserve(unsigned int, unsigned int, unsigned int, llama_memory_context_i const*, bool, unsigned long*) () from /usr/lib/libllama.so.0
#9 0x00007f27946b1c76 in llama_context::sched_reserve() () from /usr/lib/libllama.so.0
#10 0x00007f27946b2df0 in llama_context::llama_context(llama_model const&, llama_context_params) () from /usr/lib/libllama.so.0
#11 0x00007f27946c3af6 in llama_init_from_model () from /usr/lib/libllama.so.0
#12 0x000055ca83e568a8 in ?? ()
#13 0x000055ca83e5abdf in ?? ()
#14 0x000055ca83daef7b in ?? ()
#15 0x00007f2793427c0e in ?? () from /usr/lib/libc.so.6
#16 0x00007f2793427d4b in __libc_start_main () from /usr/lib/libc.so.6
#17 0x000055ca83dba7c5 in ?? ()
[Inferior 1 (process 45127) detached]
Name and Version
version: 8351 (77efcba)
built with GNU 15.2.1 for Linux x86_64
Operating systems
Linux
GGML backends
CPU
Hardware
AMD RYZEN AI MAX+ 395 w/ Radeon 8060S
Models
https://huggingface.co/bartowski/nvidia_Nemotron-3-Nano-30B-A3B-GGUF
https://huggingface.co/unsloth/Nemotron-3-Nano-30B-A3B-GGUF
Problem description & steps to reproduce
When I try running a GGUF quantization of Nemotron 3 Nano, I get the following assertion error. The device does not change this error (occurs on CPU, ROCm, and Vulkan). It happens regardless of the llama.cpp executable used (llama-cli, llama-bench, and llama-completion):
First Bad Commit
No response
Relevant log output
Logs