invoke-ai/InvokeAI · error · NotAMatchError

Wan A14B GGUF filename or metadata must identify the model a

Error message

Wan A14B GGUF filename or metadata must identify the model as Wan 2.2

What it means

Raised when the detected Wan variant is an A14B MoE model (T2V_A14B or I2V_A14B) but 'wan22' is absent from the normalized identity string built from the filename stem plus GGUF general.name metadata. A14B GGUFs must self-identify as Wan 2.2 because Wan 2.1 also ships A14B architectures, and the loader must not mix 2.1 expert files into a 2.2 setup.

Source

Thrown at invokeai/backend/model_manager/configs/main.py:2229

            raise NotAMatchError(unsupported_reason)
        gguf_name = mod.metadata().get("general.name", "")
        normalized_identity = "".join(
            character for character in f"{mod.path.stem} {gguf_name}".lower() if character.isalnum()
        )
        if "wan21" in normalized_identity:
            raise NotAMatchError("Wan 2.1 GGUF models are not supported by the Wan 2.2 loader")
        # A misnamed Wan 2.1 GGUF slips past the name check above; the architectural
        # markers don't care what the file is called.
        wan_2_1_reason = _find_wan_2_1_marker(sd)
        if wan_2_1_reason is not None:
            raise NotAMatchError(f"Wan 2.1 GGUF models are not supported by the Wan 2.2 loader: {wan_2_1_reason}")

        explicit_variant = override_fields.pop("variant", None)
        variant = explicit_variant or _detect_wan_variant_from_state_dict(sd)
        if variant is None:
            raise NotAMatchError("could not determine Wan variant from state dict")
        if variant in (WanVariantType.T2V_A14B, WanVariantType.I2V_A14B) and "wan22" not in normalized_identity:
            raise NotAMatchError("Wan A14B GGUF filename or metadata must identify the model as Wan 2.2")

        expert = _resolve_wan_expert(mod, override_fields, variant)

        return cls(**override_fields, variant=variant, expert=expert)


class Main_Checkpoint_Wan_Config(Checkpoint_Config_Base, Main_Config_Base, Config_Base):
    """Model config for single-file Wan 2.2 transformer checkpoints (safetensors).

    This is the format the community ships on CivitAI and in ComfyUI-oriented
    Hugging Face repos: one ``.safetensors`` per transformer, in either the native
    upstream key layout or the diffusers one, optionally under a
    ``model.diffusion_model.`` prefix, and optionally ComfyUI ``fp8_scaled``
    quantized. The loader normalises all of those.

    As with GGUF, A14B's MoE arrives as two files (one per expert); ``expert``
    records which one this is so the Wan model loader invocation can pair them.
    TI2V-5B is single-transformer and stores ``expert='none'``.

View on GitHub (pinned to 0b6a024f2f)

Solutions

1. Rename the file to include 'wan2.2' (e.g. Wan2.2-I2V-A14B-high-noise-Q4_K_M.gguf) and rescan
2. If the GGUF metadata is missing general.name, prefer fixing the filename — the metadata only complements it
3. Confirm the model really is Wan 2.2; if it is actually a renamed 2.1 A14B, the architectural check may catch it and the file is unusable regardless

Example fix

// before
# mv high-noise-Q4_K_M.gguf autoimport/main/
// after
# mv high-noise-Q4_K_M.gguf autoimport/main/Wan2.2-I2V-A14B-high-noise-Q4_K_M.gguf && rescan

identity = ''.join(c for c in (path.stem + gguf_general_name).lower() if c.isalnum())
if 'a14b' in identity and 'wan22' not in identity:
    print(f'{path.name}: rename to include wan2.2 (and which expert) before importing')

try:
    import_model(path)
except NotAMatchError as e:
    if 'must identify the model as Wan 2.2' in str(e):
        new = path.with_name('Wan2.2-' + path.name)
        path.rename(new)
        import_model(new)
    else:
        raise

When it happens

Trigger: Importing a Wan A14B GGUF whose filename and metadata don't mention wan22 — e.g. plain 'high-noise-Q4_K_M.gguf' or a name reading just 'wan-t2v-14b'; files renamed aggressively for download mirrors.

Common situations: Stripping original names when organizing model folders; sites that rename files to SEO slugs; metadata-stripped GGUF repacks.

Related errors

• state dict does not look like a Wan transformer
• state dict has no undecorated transformer block weights — it
• {unsupported_reason}
• Wan 2.1 GGUF models are not supported by the Wan 2.2 loader
• Wan 2.1 GGUF models are not supported by the Wan 2.2 loader:

AI-assisted analysis of invoke-ai/InvokeAI@0b6a024f2f (2026-08-29). Data as JSON: /api/errors/1fe19c3917e1c7d2. Report an issue: GitHub.