Know when to switch, route, or hold your production LLM.
Prompt CI validates every prompt change against your real production traffic before it ships, and standing Monitors do the same for every new model. Quality retained is the gate; savings are the receipt. Every Run updates a living switch / route / hold verdict, delivered to Slack, your webhook, or straight back onto the trace in Langfuse or Braintrust.
One sponsored comparison · 200+ models · No contract
200+
Models Supported
15+
LLM Providers
6
Tracing Tools Supported
<5 min
First Results in Minutes
Monitors
Ship model changes with evidence, not guesswork
Connect production traffic to a Monitor. PeerLM compares candidates against a frozen control, then rolls quality retained and projected savings into a living switch / route / hold verdict.
Sources
OpenTelemetry, Langfuse, Braintrust, LangSmith, Helicone, Cloudflare AI Gateway, direct API, or file upload. Sync production traffic into each Monitor — no app rewrite required.
Observed or Replayed Control
Observed control compares challengers with the exact captured production response and makes no incumbent call. Replayed control explicitly generates both sides as they behave today.
Auto-Runs & Triggers
Weekly heartbeat, plus catalog, price, drift, and a deploy trigger on every paid plan. Run allowances keep the month bounded.
Living Verdict
Switch, route, or hold — refreshed by every Run. Quality retained, projected savings, and latency are evaluated against a frozen decision contract; evidence strength only describes support for the result.
Standing monitors start on Pro. Inference is included — you buy monitors and runs, not tokens.
Why PeerLM
Judges you don't pick, on prompts you didn't write
PeerLM seats the panel and a model from the vendor under test can never judge it. Every comparison runs in both response positions, on prompts sampled from your own production traffic.
Make Decisions More Bias-Resistant
Every challenger is compared with your control in both response positions, by a cross-provider panel that excludes the vendors under test.
Get Granular, Exportable Performance Data
Structured JSON scoring means each item is scored independently — not buried in free-text prose. Export directly to your analytics stack or data warehouse.
Test Every Model Against Real User Scenarios
Define personas with unique system prompts and criteria, then see exactly which model excels for which audience. No more one-size-fits-all benchmarks.
See Which Model Wins for Each Use Case
Per-persona leaderboards with best/worst performer identification, model rankings, and score distributions — the reporting quality your stakeholders expect.
Cut Costs with Smart Response Caching
Identical prompts reuse cached responses instead of regenerating. Edit a prompt and the cache auto-invalidates — iterate without waiting on the same generations twice.
Improve Repeatability and Traceability
Pin temperature to 0 and fix seeds where supported. Capability checks send only valid parameters, and each run records what was actually used.
How It Works
From configuration to insight in minutes
Set up an evaluation in minutes. Get results you can present to leadership.
Configure Your Evaluation
Pick models, define personas, set topics — minutes, not days. Start from a template or build from scratch.
Run Blind Comparisons
Each challenger is compared with the control in both positions, by judges drawn from providers with nothing at stake in the result.
Review Decision-Ready Evidence
Per-persona leaderboards, score matrices, and exportable reports. Share publicly or pipe into your data warehouse as CSV/JSON.
Before & After
What changes when guesswork ends
Without PeerLM
With PeerLM
Flipping between ChatGPT and Claude tabs, hoping you'll 'just know'
Automated blind ranking across dozens of real-world scenarios
Arbitrary 1–10 scores nobody can reproduce or defend
Relative ranking that surfaces true performance gaps
One prompt, tested once, by one person on a Friday afternoon
Batch evaluation across personas, topics, and criteria
'We went with GPT because… the team already had it open'
Audit-ready data your CTO and CFO can stand behind
Paying premium rates for models that underperform cheaper ones
Projected savings paired with quality retained before a switch verdict
Manually re-evaluating every time a provider drops a new model
Automatic comparison Runs triggered by model releases, price changes, and quality drift
Pricing
Simple, transparent pricing
Monitors, runs, and Prompt CI — model inference included. No contracts — cancel anytime.
Free
one sponsored comparison
One sponsored comparison on your own prompts.
Start Sponsored Comparison- 1 sponsored comparison, judged and scored
- Standard & Advanced models
- Directional result — 5 judges on a handful of examples
- Reports guaranteed available for 7 days
Pro
per organization · unlimited seats
Every prompt and model change checked against your real traffic.
Upgrade to Pro- Prompt CI — deploy webhook and GitHub Action
- Up to 2 monitors · 10 organization-pooled runs/mo
- Weekly, plus catalog, price, drift and deploy triggers
- 150 of your own prompts, 2 candidates per run
Team
per organization · unlimited seats
Premium judges and the volume to gate every deploy.
Upgrade to Team- Everything in Pro
- Premium judge pool — the strongest evidence we'll seat
- Up to 6 monitors · 60 organization-pooled runs/mo
- Prompt-as-variable runs
Enterprise
10 monitors · 100 pooled runs default
Frontier models, your own judges, and your own provider keys.
Start with a Free Managed TrialTalk to sales →- Everything in Team
- Frontier models as candidates
- Choose your own judges
- Bring your own provider keys — judges and candidates both
Standing monitors and Prompt CI both start on Pro. Inference is included in every paid plan.
Compare all plan featuresGet a free benchmark report for your team.
We'll run blind evaluations with your real prompts and deliver a report with clear model recommendations. Free for qualified teams.
One sponsored comparison · 200+ models · No contract