# How to Resolve "Failed to Load Weights" Errors with Engine Version Mismatch in Needle

> Fix Needle 'failed to load weights' errors caused by engine version mismatch. Learn how to rebuild checkpoints or align your Needle installation to resolve this common issue.

- Repository: [Cactus Compute, Inc./needle](https://github.com/cactus-compute/needle)
- Tags: how-to-guide
- Published: 2026-08-18

---

**The "failed to load weights" error occurs when a checkpoint's `format_version` does not match the `CHECKPOINT_FORMAT_VERSION` constant (currently `2`) defined in [`needle/model/run.py`](https://github.com/cactus-compute/needle/blob/main/needle/model/run.py), requiring you to rebuild the checkpoint or align your Needle installation with the checkpoint's creation version.**

Needle, the open-source inference engine from Cactus Compute, enforces strict checkpoint compatibility through a format version validation system. When you attempt to load a model checkpoint created with a different engine version, the library immediately rejects it to prevent runtime incompatibilities. Understanding the version check implemented in the source code is essential for resolving these loading errors efficiently.

## Understanding the Checkpoint Format Version Check

The root cause of the error lies in the validation logic inside [`needle/model/run.py`](https://github.com/cactus-compute/needle/blob/main/needle/model/run.py). The `load_checkpoint` function extracts a `format_version` field from the checkpoint header and compares it against the constant `CHECKPOINT_FORMAT_VERSION`, defined as `2` on lines 13-15. When these values differ, the code raises a descriptive `ValueError`:

```python
if version != CHECKPOINT_FORMAT_VERSION:
    raise ValueError(
        f"{path} is not a format‑v{CHECKPOINT_FORMAT_VERSION} checkpoint "
        f"(got format_version={version!r}). Old encoder‑decoder/tool‑calling "
        f"checkpoints are incompatible with this branch."
    )

```

*Source:* [[`needle/model/run.py`](https://github.com/cactus-compute/needle/blob/main/needle/model/run.py) lines 86-90](https://github.com/cactus-compute/needle/blob/main/needle/model/run.py#L86-L90)

This check ensures that **only checkpoints serialized with the current library format** can initialize the engine, preventing silent failures from schema mismatches.

## Identifying the Version Mismatch

Before applying fixes, confirm the versions involved. Check your installed Needle version programmatically:

```python
import needle
print(needle.__version__)  # Defined in needle/__init__.py lines 85-87

```

*Source:* [[`needle/__init__.py`](https://github.com/cactus-compute/needle/blob/main/needle/__init__.py)](https://github.com/cactus-compute/needle/blob/main/needle/__init__.py#L85-L87)

When loading fails, the error message explicitly states the expected format version versus the version found in your checkpoint file. For example, if the checkpoint reports `format_version=1` while the library expects `2`, the mismatch is confirmed.

## Three Methods to Resolve the Error

You have three primary approaches to align the checkpoint format with the library's expectations.

### Rebuild the Checkpoint with the Current Needle Version

The recommended solution uses the **`needle build`** command to regenerate the checkpoint using your current library version. This process re-serializes the weights with the correct `CHECKPOINT_FORMAT_VERSION`:

```bash

# Convert an old or incompatible checkpoint to the current format

needle build --ckpt old_checkpoint.ckpt --out compatible_checkpoint.cact

```

After rebuilding, load the new checkpoint without errors:

```python
import needle
agent = needle.Needle(weights="compatible_checkpoint.cact")
result = agent.complete("Explain quantum computing")

```

### Match Your Needle Version to the Checkpoint

If you cannot rebuild the checkpoint, install the Needle version that matches its creation format. For legacy checkpoints requiring format version `1`, downgrade your installation:

```bash
pip install "needle<2.0.0"

```

Verify compatibility by loading the weights:

```python
import needle

# This will succeed only when versions align

model = needle.Needle(weights="legacy_checkpoint.cact")

```

### Convert Checkpoints Programmatically

For batch conversions or custom pipelines, load the checkpoint with the older compatible library version and immediately re-save it using the newer version:

```python
import needle

# Load with the version that matches the checkpoint's format

legacy_model = needle.Needle(weights="old_format.cact")

# Re-save automatically writes the current CHECKPOINT_FORMAT_VERSION

legacy_model.save("upgraded_format.cact")

```

The newly saved file contains the updated format version header required by current Needle releases.

## Handling Errors in the Playground UI

When using the Needle Playground interface, the same validation occurs through the `Engine.load_weights` method in [`playground/server.py`](https://github.com/cactus-compute/needle/blob/main/playground/server.py) (lines 48-55). If you encounter the error in the web UI, apply one of the resolution methods above, then restart the server and reload your weights using the upload button.

## Summary

- Needle checkpoints include a **`format_version`** field that must match the library's **`CHECKPOINT_FORMAT_VERSION`** constant (currently `2`).
- The validation occurs in **[`needle/model/run.py`](https://github.com/cactus-compute/needle/blob/main/needle/model/run.py)** within the `load_checkpoint` function, which raises a `ValueError` on any mismatch.
- **Rebuild** checkpoints using `needle build` to upgrade them to the current format while preserving the underlying weights.
- **Downgrade** your Needle installation to match legacy checkpoint formats when rebuilding is not feasible.
- **Convert** programmatically by loading with an older library version and saving with the current one to bridge format differences.

## Frequently Asked Questions

### What is the current CHECKPOINT_FORMAT_VERSION in Needle?

The current `CHECKPOINT_FORMAT_VERSION` is defined as **`2`** in [`needle/model/run.py`](https://github.com/cactus-compute/needle/blob/main/needle/model/run.py) (lines 13-15). All checkpoints created with recent Needle versions use this format, while older checkpoints may use version `1` or other legacy formats that are explicitly rejected by the current loader.

### Can I load a checkpoint created with Needle 1.x using Needle 2.x?

No. According to the source code in [`needle/model/run.py`](https://github.com/cactus-compute/needle/blob/main/needle/model/run.py) (lines 86-90), Needle 2.x explicitly rejects checkpoints with a `format_version` other than `2`. The error message states that "old encoder-decoder/tool-calling checkpoints are incompatible with this branch." You must either rebuild the checkpoint using a current version of the `needle build` tool or downgrade your Needle installation to the version used to create the checkpoint.

### Where does the "failed to load weights" error originate in the codebase?

The error originates in the **`load_checkpoint`** function in **[`needle/model/run.py`](https://github.com/cactus-compute/needle/blob/main/needle/model/run.py)** when the checkpoint's extracted version does not match `CHECKPOINT_FORMAT_VERSION`. If you are using the Playground UI, the error propagates through **`Engine.load_weights`** in [`playground/server.py`](https://github.com/cactus-compute/needle/blob/main/playground/server.py) (lines 48-55), which wraps the underlying checkpoint loading logic.

### How do I verify which format version a checkpoint uses?

Attempt to load the checkpoint in a Python session; the resulting `ValueError` explicitly states the format version found in the file versus the expected version (e.g., "got format_version='1'"). Alternatively, you can inspect the checkpoint file's metadata header if available, though the error message from the Needle loader provides the most reliable identification.