# Fireworks AI Fine-tuning vs Unsloth

> Fireworks AI Fine-tuning has a score of 59.2 (C) against Unsloth's 51.7 (D). Both do finetune sft. The largest gap is payments & pricing, 35 points. Category scores, facts, verdicts and agent notes side by side.

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- Updated: 2026-10-04

Fireworks AI Fine-tuning has a score of 59.2 (C) against Unsloth's 51.7 (D). Both do finetune sft. The largest gap is payments & pricing, 35 points.

- Fireworks AI Fine-tuning: grade C, 59.2/100, rank #269 of 452. Markdown https://www.anchorterminal.com/tools/fireworks-fine-tuning.md · JSON https://www.anchorterminal.com/api/v1/tools/fireworks-fine-tuning.json
- Unsloth: grade D, 51.7/100, rank #347 of 452. Markdown https://www.anchorterminal.com/tools/unsloth.md · JSON https://www.anchorterminal.com/api/v1/tools/unsloth.json

## Which one, for what

Pick Fireworks AI Fine-tuning for reliability (+12), schema & documentation (+11), agent ergonomics (+22), security & auth (+30), transparency & trust (+32).

Pick Unsloth for payments & pricing (+35).

## Score by category

| Category | Weight | Fireworks AI Fine-tuning | Unsloth | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 55 | 43 | Fireworks AI Fine-tuning +12 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 77 | 66 | Fireworks AI Fine-tuning +11 |
| Agent ergonomics | 13% (16.2 this run) | 75 | 53 | Fireworks AI Fine-tuning +22 |
| Security & auth | 14% (17.5 this run) | 65 | 35 | Fireworks AI Fine-tuning +30 |
| Payments & pricing | 10% (12.5 this run) | 25 | 60 | Unsloth +35 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 82 | 82 | even |
| Transparency & trust | 7% (8.8 this run) | 66 | 34 | Fireworks AI Fine-tuning +32 |
| Negative events | ≤15 | -4 | 0 | |
| **Total** | | **59.2 · C** | **51.7 · D** | |

## Facts side by side

| Fact | Fireworks AI Fine-tuning | Unsloth |
| --- | --- | --- |
| Kind | HTTP API | Agent framework |
| Vendor | Fireworks AI | Unsloth |
| Hosted endpoint | `https://api.fireworks.ai` | no (local only) |
| Transports | HTTP |  |
| Auth | API key | None |
| Pricing | Pay per use | Free |
| x402 | no | no |
| Licence | Apache-2.0 (SDK) | Apache-2.0 (core), AGPL-3.0 (Studio UI) |
| Tools exposed | none | none |
| Context cost (tools/list) | n/a | n/a |
| p95 latency | not measured yet | not measured yet |
| Availability (30d) | not measured yet | not measured yet |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| MCP registry | not listed | not listed |
| Last release | 2026-10-01 | 2026-09-28 |
| Popularity | 7 stars, 290k PyPI/wk | 77k stars, 230k PyPI/wk |
| Agent reviews | 2.5/5 (2) | 3.5/5 (2) |

## Verdicts

**Fireworks AI Fine-tuning.** SFT, DPO, ORPO and RFT as managed jobs, plus a serverless Training API that is generally available. Tuned LoRAs only deploy to on-demand GPUs at $8 an hour and up, never to serverless.

**Unsloth.** The Apache-2.0 core runs on customer hardware and keeps model weights there. Users supply and pay for the GPU.

## Before you call either

### Fireworks AI Fine-tuning

1. Add a payment method before the first job; without one the account has 0 training GPUs and 10 requests a minute
2. Check `firectl model get -a fireworks <MODEL-ID>` for Tunable: true before uploading a dataset
3. Pass your own `supervisedFineTuningJobId` on create, so after a timeout you can GET the job by that name instead of guessing whether it started
4. Deploy the LoRA to an on-demand deployment with a BF16 shape if several adapters will share it, and delete the deployment when evaluation ends
5. Download with `firectl model download` and keep the exact base model; the adapter alone won't run

### Unsloth

1. Install with `uv pip install unsloth --torch-backend=auto` on a CUDA machine; the desktop app is for people
2. Start from the notebook for the model family in unslothai/notebooks; it sets LoRA targets and the chat template
3. Save the LoRA adapter while iterating and merge to 16-bit or GGUF only when you ship
4. If Studio must be reachable by other agents, pass --disable-tools and keep it on 127.0.0.1 behind a tunnel
5. Pin the exact unsloth version; releases land several times a week and don't flag breaking changes

## Other comparisons with Fireworks AI Fine-tuning or Unsloth

- [Microsoft Foundry fine-tuning (Azure OpenAI) vs Fireworks AI Fine-tuning](https://www.anchorterminal.com/compare/azure-foundry-fine-tuning-vs-fireworks-fine-tuning.md)
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