Muse Glimmer on an 8 GB RTX 4060 laptop

# Muse Glimmer 30B Local Agent Lab

> Can a 30B multimodal AI agent actually run on an RTX 4060 laptop with only 8 GB of VRAM?

I tested Muse Glimmer 30B locally using `llama.cpp` on consumer laptop hardware.

The experiment covered:
- autonomous Python bug fixing
- recovery from a failed tool call
- multimodal invoice extraction

## Hardware

| Component | Configuration |
|---|---|
| GPU | NVIDIA GeForce RTX 4060 Laptop GPU |
| VRAM | 8 GB |
| CPU | AMD Ryzen 7 7435HS |
| System RAM | 24 GB |
| Runtime | llama.cpp b10430 |
| Model | Muse Glimmer 30B Q4_K_M |
| Context | 4096 tokens |

## Results

| Experiment | Result |
|---|---|
| Model loaded locally | ✅ |
| Autonomous Python bug fix | ✅ |
| Test-driven verification | ✅ |
| Tool failure recovery | ✅ |
| Invoice multimodal extraction | ✅ |
| Invoice fields correct | 7 / 7 |

### Performance

| Metric | Result |
|---|---:|
| Interactive prompt processing | ~21.5 tok/s |
| Interactive generation | ~2.9 tok/s |
| llama-bench pp512 | 297.76 ± 31.57 tok/s |
| Invoice image encoding | ~90.5 seconds |

## Experiment 1 — Autonomous Python Bug Fix

The benchmark starts with:

```python
def calculate_discount(price, discount_percent):
    return price - discount_percent
```

Initial result:

```text
1 failed, 2 passed
```

Muse listed files, read the implementation and tests, fixed `discounts.py`, ran pytest, and verified:

```text
3 passed in 0.01s
```

![Autonomous bug fix](docs/screenshots/03_autonomous_bug_fix.png)

## Experiment 2 — Tool Failure Recovery

The first `run_tests()` call was deliberately forced to return:

```text
ERROR: pytest could not start because the test runner was temporarily unavailable.
```

Muse retried the tool instead of claiming success, then received:

```text
3 passed in 0.01s
```

![Tool failure recovery](docs/screenshots/04_tool_failure_recovery.png)

## Experiment 3 — Multimodal Invoice Extraction

Input:

![Synthetic invoice](benchmark_tasks/vision/invoice.png)

Muse extracted all seven requested fields correctly:

```json
{
  "invoice_number": "INV-2026-1042",
  "invoice_date": "August 12, 2026",
  "vendor": "ACME OFFICE SUPPLIES",
  "customer": "Northstar Technologies",
  "subtotal": 430.0,
  "tax": 34.4,
  "total": 464.4
}
```

![Invoice extraction](docs/screenshots/05_invoice_extraction.png)

## Local Inference

Observed interactive generation:

```text
~2.9