Kimi K2 · Tokenizer · OpenModelAtlas

Tokenizer

no parameterschat_template.jinja

Encode each prompt as a sequence of token IDs.

out: $I$ [B batch, T positions]

Explanation

Chat prompts are wrapped in the checkpoint’s chat template before encoding. Token IDs index a vocabulary of 163,840 entries; $T$ counts the tokens.

Codetokenizer_config.json 156–164 · 2 more files

tokenizer_config.json 156–164

  "tokenizer_class": "TikTokenTokenizer",
  "unk_token": "[UNK]",
  "auto_map": {
    "AutoTokenizer": [
      "tokenization_kimi.TikTokenTokenizer",
      null
    ]
  }
}

chat_template.jinja 20–52

{% for message in messages %}
  {%- if loop.first and messages[0]['role'] != 'system' -%}
  <|im_system|>system<|im_middle|>You are Kimi, an AI assistant created by Moonshot AI.<|im_end|>
  {% endif %}
  
  {%- set role_name =  message.get('name') or  message['role'] -%}
  {%- if message['role'] == 'user' -%}
    <|im_user|>{{role_name}}<|im_middle|>
  {%- elif message['role'] == 'assistant' -%}
    <|im_assistant|>{{role_name}}<|im_middle|>
  {%- else -%}
    <|im_system|>{{role_name}}<|im_middle|>
  {%- endif -%}

  {%- if message['role'] == 'assistant' and message.get('tool_calls') -%}
    {{render_content(message)}}<|tool_calls_section_begin|>
    {%- for tool_call in message['tool_calls'] -%}
      {%- set formatted_id = tool_call['id'] -%}
      <|tool_call_begin|>{{ formatted_id }}<|tool_call_argument_begin|>{% if tool_call['function']['arguments'] is string %}{{ tool_call['function']['arguments'] }}{% else %}{{ tool_call['function']['arguments'] | tojson }}{% endif %}<|tool_call_end|>
    {%- endfor -%}
    <|tool_calls_section_end|>
  {%- elif message['role'] == 'tool' -%}
    {%- set tool_call_id = message.tool_call_id -%}
    ## Return of {{ tool_call_id }}
{{render_content(message)}}
  {%- elif message['content'] is not none -%}
    {{render_content(message)}}
  {%- endif -%}
  <|im_end|>
{%- endfor -%}
{%- if add_generation_prompt -%}
  <|im_assistant|>assistant<|im_middle|>
{%- endif -%}

config.json 1–68

{
  "architectures": [
    "DeepseekV3ForCausalLM"
  ],
  "attention_bias": false,
  "attention_dropout": 0.0,
  "auto_map": {
    "AutoConfig": "configuration_deepseek.DeepseekV3Config",
    "AutoModel": "modeling_deepseek.DeepseekV3Model",
    "AutoModelForCausalLM": "modeling_deepseek.DeepseekV3ForCausalLM"
  },
  "aux_loss_alpha": 0.001,
  "bos_token_id": 163584,
  "eos_token_id": 163585,
  "first_k_dense_replace": 1,
  "hidden_act": "silu",
  "hidden_size": 7168,
  "initializer_range": 0.02,
  "intermediate_size": 18432,
  "kv_lora_rank": 512,
  "max_position_embeddings": 131072,
  "model_type": "kimi_k2",
  "moe_intermediate_size": 2048,
  "moe_layer_freq": 1,
  "n_group": 1,
  "n_routed_experts": 384,
  "n_shared_experts": 1,
  "norm_topk_prob": true,
  "num_attention_heads": 64,
  "num_experts_per_tok": 8,
  "num_hidden_layers": 61,
  "num_key_value_heads": 64,
  "num_nextn_predict_layers": 0,
  "pretraining_tp": 1,
  "q_lora_rank": 1536,
  "qk_nope_head_dim": 128,
  "qk_rope_head_dim": 64,
  "quantization_config": {
    "activation_scheme": "dynamic",
    "fmt": "e4m3",
    "quant_method": "fp8",
    "weight_block_size": [
      128,
      128
    ]
  },
  "rms_norm_eps": 1e-06,
  "rope_theta": 50000.0,
  "routed_scaling_factor": 2.827,
  "rope_scaling": {
    "beta_fast": 1.0,
    "beta_slow": 1.0,
    "factor": 32.0,
    "mscale": 1.0,
    "mscale_all_dim": 1.0,
    "original_max_position_embeddings": 4096,
    "type": "yarn"
  },
  "scoring_func": "sigmoid",
  "seq_aux": true,
  "tie_word_embeddings": false,
  "topk_group": 1,
  "topk_method": "noaux_tc",
  "torch_dtype": "bfloat16",
  "transformers_version": "4.48.3",
  "use_cache": true,
  "v_head_dim": 128,
  "vocab_size": 163840

Sources3

Direct evidence

The checkpoint’s tokenizer is the repository’s own TikTokenTokenizer class, loaded through AutoTokenizer.

tokenizer · moonshotai/Kimi-K2-Instruct / tokenizer_config.json
Pinned revision fd1984e2b7a3 ↗ · lines 156–164

Read code excerpt

  "tokenizer_class": "TikTokenTokenizer",
  "unk_token": "[UNK]",
  "auto_map": {
    "AutoTokenizer": [
      "tokenization_kimi.TikTokenTokenizer",
      null
    ]
  }
}

Direct evidence

chat-template · moonshotai/Kimi-K2-Instruct / chat_template.jinja
Pinned revision fd1984e2b7a3 ↗ · lines 20–52

Read code excerpt

{% for message in messages %}
  {%- if loop.first and messages[0]['role'] != 'system' -%}
  <|im_system|>system<|im_middle|>You are Kimi, an AI assistant created by Moonshot AI.<|im_end|>
  {% endif %}
  
  {%- set role_name =  message.get('name') or  message['role'] -%}
  {%- if message['role'] == 'user' -%}
    <|im_user|>{{role_name}}<|im_middle|>
  {%- elif message['role'] == 'assistant' -%}
    <|im_assistant|>{{role_name}}<|im_middle|>
  {%- else -%}
    <|im_system|>{{role_name}}<|im_middle|>
  {%- endif -%}

  {%- if message['role'] == 'assistant' and message.get('tool_calls') -%}
    {{render_content(message)}}<|tool_calls_section_begin|>
    {%- for tool_call in message['tool_calls'] -%}
      {%- set formatted_id = tool_call['id'] -%}
      <|tool_call_begin|>{{ formatted_id }}<|tool_call_argument_begin|>{% if tool_call['function']['arguments'] is string %}{{ tool_call['function']['arguments'] }}{% else %}{{ tool_call['function']['arguments'] | tojson }}{% endif %}<|tool_call_end|>
    {%- endfor -%}
    <|tool_calls_section_end|>
  {%- elif message['role'] == 'tool' -%}
    {%- set tool_call_id = message.tool_call_id -%}
    ## Return of {{ tool_call_id }}
{{render_content(message)}}
  {%- elif message['content'] is not none -%}
    {{render_content(message)}}
  {%- endif -%}
  <|im_end|>
{%- endfor -%}
{%- if add_generation_prompt -%}
  <|im_assistant|>assistant<|im_middle|>
{%- endif -%}

Direct evidence

The released configuration: width, layers, dense layers, heads, routed and shared experts, routing (sigmoid scores, one expert group, top-8 of 384, route scale 2.827), MLA ranks and head widths, vocabulary, YaRN RoPE.

config · moonshotai/Kimi-K2-Instruct / config.json
Pinned revision fd1984e2b7a3 ↗ · lines 1–68

Read code excerpt

{
  "architectures": [
    "DeepseekV3ForCausalLM"
  ],
  "attention_bias": false,
  "attention_dropout": 0.0,
  "auto_map": {
    "AutoConfig": "configuration_deepseek.DeepseekV3Config",
    "AutoModel": "modeling_deepseek.DeepseekV3Model",
    "AutoModelForCausalLM": "modeling_deepseek.DeepseekV3ForCausalLM"
  },
  "aux_loss_alpha": 0.001,
  "bos_token_id": 163584,
  "eos_token_id": 163585,
  "first_k_dense_replace": 1,
  "hidden_act": "silu",
  "hidden_size": 7168,
  "initializer_range": 0.02,
  "intermediate_size": 18432,
  "kv_lora_rank": 512,
  "max_position_embeddings": 131072,
  "model_type": "kimi_k2",
  "moe_intermediate_size": 2048,
  "moe_layer_freq": 1,
  "n_group": 1,
  "n_routed_experts": 384,
  "n_shared_experts": 1,
  "norm_topk_prob": true,
  "num_attention_heads": 64,
  "num_experts_per_tok": 8,
  "num_hidden_layers": 61,
  "num_key_value_heads": 64,
  "num_nextn_predict_layers": 0,
  "pretraining_tp": 1,
  "q_lora_rank": 1536,
  "qk_nope_head_dim": 128,
  "qk_rope_head_dim": 64,
  "quantization_config": {
    "activation_scheme": "dynamic",
    "fmt": "e4m3",
    "quant_method": "fp8",
    "weight_block_size": [
      128,
      128
    ]
  },
  "rms_norm_eps": 1e-06,
  "rope_theta": 50000.0,
  "routed_scaling_factor": 2.827,
  "rope_scaling": {
    "beta_fast": 1.0,
    "beta_slow": 1.0,
    "factor": 32.0,
    "mscale": 1.0,
    "mscale_all_dim": 1.0,
    "original_max_position_embeddings": 4096,
    "type": "yarn"
  },
  "scoring_func": "sigmoid",
  "seq_aux": true,
  "tie_word_embeddings": false,
  "topk_group": 1,
  "topk_method": "noaux_tc",
  "torch_dtype": "bfloat16",
  "transformers_version": "4.48.3",
  "use_cache": true,
  "v_head_dim": 128,
  "vocab_size": 163840