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Evidence-backed savings when quality holds

Know when to switch, route, or hold your production LLM.

PeerLM Monitors compare challengers on your production traffic, verify quality retained, and show projected savings beside a separate evidence-strength score. Every Run updates a living switch / route / hold verdict. Blind evaluation across 200+ models remains available for authored comparisons.

One sponsored comparison  ·  200+ models  ·  No contract

200+

Models Supported

15+

LLM Providers

Position-Swapped Judging

<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

SDK, file upload, Langfuse, Helicone, Cloudflare AI Gateway, or OpenTelemetry. 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, and drift. Team adds deploy triggers for Prompt CI. 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

Blind evaluation remains powerful supporting proof

Explore 200+ models with anonymized, shuffled Suite rankings. Production Monitors add paired position swaps and cross-provider judging.

Make Decisions More Bias-Resistant

Suites anonymize and shuffle model outputs. Monitors add paired position swaps and cross-provider panels that exclude 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.

1

Configure Your Evaluation

Pick models, define personas, set topics — minutes, not days. Start from a template or build from scratch.

2

Run Blind Comparisons

Suites anonymize and shuffle ranked outputs. Monitors compare each challenger with the control in both positions using cross-provider judges.

3

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 triggers — model inference included. No contracts — cancel anytime.

Free

$0

one sponsored comparison

  • 1 sponsored comparison
  • Standard + Advanced models
  • 5 judges, directional result
  • 1 seat
  • Reports for 7 days
Start Sponsored Comparison
Most Popular

Pro

$99/mo

2 monitors · 10 pooled runs/mo

  • 150 prompts, 2 candidates
  • 5 judges from a pool of 8
  • Weekly + catalog, price, drift
  • Inference included
  • Premium candidates, API & MCP
Upgrade to Pro

Team

$499/mo

6 monitors · 60 pooled runs/mo

  • Everything in Pro
  • Prompt CI & GitHub Action
  • Deploy triggers, no debounce
  • Prompt-as-variable runs
  • Reports for 180 days
Upgrade to Team

Enterprise

From $36k

10 monitors · 100 pooled runs default

  • Everything in Team
  • Frontier candidates
  • Choose your own judges
  • BYOK — judges and candidates
  • Dedicated support & SLA
Start with a Free Managed Trial

Standing monitors start on Pro. Inference is included in every paid plan.

Compare all plan features

Get 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