Overview
Your training workspace at a glance.
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Build a training environment and launch your first run to start improving your model.
Post-Training
Built for your Agent.
freesolo.co/platform
/Freesolo/people-searchT
Overview
Your training workspace at a glance.
Environments0
Runs0
Models0
No training runs yet
Build a training environment and launch your first run to start improving your model.
Agentnative.Builtforengineers.
Researchers want a loop to tune. You want a model in prod. Point your agent at Flash and a finished, deployable model comes back.
Three steps. All in natural language.
01
02
03
Describe the run
Your agent names the model and task, and points at your data.
Approve the price
Flash returns one fixed quote and an ETA before anything runs. Say go.
Own the model
A deployable model comes back, weights exported to your repo.
01
Describe the run
Your agent names the model and task, and points at your data.
02
Approve the price
Flash returns one fixed quote and an ETA before anything runs. Say go.
03
Own the model
A deployable model comes back, weights exported to your repo.
Up to 8× less than metered equivalents
No per-token meter, no GPU-hour roulette. Your agent gets one quote for the whole run.
SFTQwen3.5-4B · SFT + eval
Tinker
0×
Fireworks
0.00×
Freesolo Flash
1×
RLQwen3.5-4B · GRPO
Tinker
0.0×
Prime
0.0×
Freesolo Flash
1×
Fireworks RL is free but you can’t design the reward function; RL pricing assumes an immediate reward function and changes for heavier rewards; multiples compare Flash’s fixed quote to each competitor’s metered list pricing for the same run.
Specializationbeatsthefrontier.
A sub-10B model tuned on your data beats a frontier model on your task, cheap and fast enough to retrain on the fly.
↑ Accuracy
Frontier zero-shot · 71%base · 56%0% ▲
SFTclimbs to the wall
GRPOpast the frontier
+18 ptsover the frontier
5 hoursagent → deployable model
$12pre-quoted, cheap to retrain
Buildfortrilliontokentasks.
A handful of hard prompts need the frontier. The millions of routine calls behind them are where SLMs win.
Customkernelsfortrainingatlightspeed.
We treat kernel engineering as a search problem. Each permutation is continuously optimized with an autoresearch loop to ensure maximum training throughput.
Yourdata.Yourmodel.Yourweights.
Own & export weights
Every run returns downloadable weights in standard formats. Serve them anywhere.
Your data stays isolated
Encrypted in transit and at rest, and never used to train anything but your model.
Reproducible & durable
Pinned configs and seeds, checkpointed end to end so every run always finishes.