Use the best model for the workload
Different prompts need different strengths: reasoning, tone, extraction accuracy, latency, cost, or stability.
benchmark intelligence for model routing
Stop guessing which model should answer.
TokenRoute runs your real prompt contracts across local, private, and BYOK cloud models, judges the responses, stores the evidence, and exports route decisions your systems can act on.
BenchmarkRun prompt packs against candidate models.
JudgeScore quality, latency, cost, failures, and contract fit.
RouteExport model choice, fallback order, and policy evidence.
live benchmark
prompt to route decision
evidence flow
prompt contract
Classify this support message into one category and give one short reason.
route_decision
qwen-2.5-7b
- score
- 94
- latency
- 1.28s
- fallback
- llama3.2
product philosophy
TokenRoute is the evidence layer before production routing changes.
Model choice should not be based on vendor claims, one-off demos, or whichever model is newest. It should be backed by repeatable benchmark data from the prompts your product actually runs.
Bring your providers, keep your control
Connect local Ollama, private endpoints, OpenRouter, OpenAI, Anthropic, and future providers without locking into one gateway.
Route from evidence, not opinion
Every recommendation points back to benchmark packs, judge provenance, deterministic checks, and observed provider behavior.
what it does
From prompt set to actionable model policy.
1. CapturePrompt, output contract, expected evidence, and workload category.
2. BenchmarkRun selected local, private, and BYOK cloud models asynchronously.
3. JudgeUse deterministic checks and optional LLM judges with stored provenance.
4. LearnPersist aggregate model trends without exposing raw prompts across tenants.
5. ActExport route decisions, fallback policy, JSON/CSV packs, and gateway-ready config.
why teams use it
Make model changes cheaper, safer, and easier to defend.
For app teams
Pick a model for a real workload with quality, latency, and cost evidence before changing production behavior.
For agents
Call a route-decision API instead of hardcoding a model into every workflow or toolchain.
For platform teams
Build a private benchmark library that tracks provider drift, failure rates, and category-specific strengths over time.
For cost control
Compare cheaper candidates against quality gates before routing traffic to expensive reasoning models.
integration-first
TokenRoute is glue, not another model marketplace.
It connects to the tools you already use and produces evidence-backed routing outputs that can feed gateways, CI checks, apps, and agents.
Local/privateOllama and private endpoints through a Local Connector Agent.
BYOK cloudOpenRouter, OpenAI, Anthropic, and provider adapters without TokenRoute carrying inference spend.
Gateway exportsLiteLLM-style policy export first; hot-path routing only after benchmark density exists.
Data productPrivate benchmark intelligence now, opt-in aggregate intelligence later.
Start with a benchmark pack.
Inspect the evidence, export the route policy, and make model selection measurable.