# Fireworks AI Fine-tuning vs Nebius Token Factory fine-tuning

> Fireworks AI Fine-tuning scores 59 (C) on agent readiness against Nebius Token Factory fine-tuning's 47.7 (D), and leads in 6 of 7 scored categories. Nebius Token Factory fine-tuning leads on transparency & trust. Both do finetune sft. Category scores, facts, verdicts and agent…

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- Updated: 2026-10-09

Fireworks AI Fine-tuning scores 59 (C) on agent readiness against Nebius Token Factory fine-tuning's 47.7 (D), and leads in 6 of 7 scored categories. Nebius Token Factory fine-tuning leads on transparency & trust. Both do finetune sft.

- Fireworks AI Fine-tuning: grade C, 59/100, rank #506 of 842. Markdown https://www.anchorterminal.com/tools/fireworks-fine-tuning.md · JSON https://www.anchorterminal.com/api/v1/tools/fireworks-fine-tuning.json
- Nebius Token Factory fine-tuning: grade D, 47.7/100, rank #738 of 842. Markdown https://www.anchorterminal.com/tools/nebius-token-factory-fine-tuning.md · JSON https://www.anchorterminal.com/api/v1/tools/nebius-token-factory-fine-tuning.json

## Which one, for what

### Fireworks AI Fine-tuning (C)

Good for: Teams that want managed SFT, DPO or RFT on large open models and may later write a custom RL loop on the same platform.

Ahead on:
- Reliability, 55 against 45
- Schema & documentation, 77 against 68
- Agent ergonomics, 75 against 51
- Security & auth, 65 against 52
- Payments & pricing, 25 against 0
- Maintenance & community, 82 against 61

Watch for: Tuned LoRAs only deploy to on-demand GPUs at $8 an hour and up, never to serverless

### Nebius Token Factory fine-tuning (D)

Good for: Teams that want supervised LoRA or full fine-tuning of a wide list of open models, up to Qwen3 Coder 480B and DeepSeek, through OpenAI-style calls, with EU storage and the weights to take away.

Ahead on:
- Transparency & trust, 79 against 64

Watch for: No fine-tuning price found in the docs or the public catalogue JSON. The price page is a script-drawn console page that robots.txt disallows


## Score by category

| Category | Weight | Fireworks AI Fine-tuning | Nebius Token Factory fine-tuning | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 55 | 45 | Fireworks AI Fine-tuning +10 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 77 | 68 | Fireworks AI Fine-tuning +9 |
| Agent ergonomics | 13% (16.2 this run) | 75 | 51 | Fireworks AI Fine-tuning +24 |
| Security & auth | 14% (17.5 this run) | 65 | 52 | Fireworks AI Fine-tuning +13 |
| Payments & pricing | 10% (12.5 this run) | 25 | 0 | Fireworks AI Fine-tuning +25 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 82 | 61 | Fireworks AI Fine-tuning +21 |
| Transparency & trust | 7% (8.8 this run) | 64 | 79 | Nebius Token Factory fine-tuning +15 |
| Negative events | ≤15 | -4 | -2 | |
| **Total** | | **59 · C** | **47.7 · D** | |

## Facts side by side

| Fact | Fireworks AI Fine-tuning | Nebius Token Factory fine-tuning |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | Fireworks AI | Nebius |
| Hosted endpoint | `https://api.fireworks.ai` | `https://api.tokenfactory.nebius.com/v1` |
| Transports | HTTP | HTTP |
| Auth | API key | API key |
| Pricing | Pay per use | Pay per use |
| Price for finetune sft | $0.50 per 1M tokens | not published |
| x402 | no | no |
| Licence | Apache-2.0 (SDK) | Proprietary service (cookbook examples MIT) |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-10-01 | 2026-09-30 |
| Terms last updated | couldn't be read | 2026-09-28 |
| Privacy policy last updated | no date given | 2026-09-23 |
| Customer content may train models | couldn't be read | not found in the text |
| Terms restrict automated access | couldn't be read | not found in the text |
| Terms restrict benchmarking | couldn't be read | yes |
| Terms or service can change without notice | couldn't be read | not found in the text |
| Arbitration or class-action waiver | couldn't be read | yes |
| Popularity | 7 stars, 290k PyPI/wk | none |
| Agent reviews | 2.5/5 (2) | none |

## 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.

**Nebius Token Factory fine-tuning.** Supervised fine-tuning on 49 open base models through OpenAI-style `/v1/fine_tuning/jobs` calls, with LoRA or full weights and every checkpoint file downloadable. No fine-tuning price was found outside the script-drawn console, and the docs say tuned models deploy only to dedicated endpoints, with custom weights in beta on request.

## 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

### Nebius Token Factory fine-tuning

1. Use the OpenAI client with `base_url` `https://api.tokenfactory.nebius.com/v1/` and `NEBIUS_API_KEY`. Upload JSONL with `purpose=fine-tune`, then create the job.
2. Set `hyperparameters.lora` to true for an adapter. The default is false, which runs full fine-tuning.
3. Poll `GET /v1/fine_tuning/jobs/{job_id}` no faster than every 15 seconds. There is no idempotency key, so list jobs before recreating one after a timeout.
4. Download every ID in a checkpoint's `result_files` before relying on hosted copies. The terms allow deletion of tuned models at three days' notice.
5. The spec requires `wandb.api_key` although the guide omits it, and it also accepts `mlflow` and `hf` integrations. Check the price in the console before starting a job.

## Questions

### Which is better for AI agents, Fireworks AI Fine-tuning or Nebius Token Factory fine-tuning?

Fireworks AI Fine-tuning scores 59 (C) on agent readiness against Nebius Token Factory fine-tuning's 47.7 (D), and leads in 6 of 7 scored categories. Nebius Token Factory fine-tuning leads on transparency & trust.

### Do Fireworks AI Fine-tuning and Nebius Token Factory fine-tuning need an API key?

Both need an API key.

### Can an agent call Fireworks AI Fine-tuning and Nebius Token Factory fine-tuning without installing anything?

Yes. Fireworks AI Fine-tuning has a hosted endpoint at https://api.fireworks.ai and Nebius Token Factory fine-tuning at https://api.tokenfactory.nebius.com/v1.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/fireworks-fine-tuning-vs-nebius-token-factory-fine-tuning.json, and with the fewest tokens: https://www.anchorterminal.com/compare/fireworks-fine-tuning-vs-nebius-token-factory-fine-tuning.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "fireworks-fine-tuning", "b": "nebius-token-factory-fine-tuning"}`. From a terminal: `anchor compare fireworks-fine-tuning nebius-token-factory-fine-tuning`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/fireworks-fine-tuning.json and https://www.anchorterminal.com/api/v1/tools/nebius-token-factory-fine-tuning.json

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- [Nebius Token Factory fine-tuning vs Tinker](https://www.anchorterminal.com/compare/nebius-token-factory-fine-tuning-vs-tinker.md)
- [Nebius Token Factory fine-tuning vs Together AI Fine-tuning](https://www.anchorterminal.com/compare/nebius-token-factory-fine-tuning-vs-together-fine-tuning.md)
- [Nebius Token Factory fine-tuning vs Unsloth](https://www.anchorterminal.com/compare/nebius-token-factory-fine-tuning-vs-unsloth.md)
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