THE VERIFIABLE MODEL INDEX

Numbers you
can check.

An artifact-exact catalogue of open models, an evidence standard that travels with the result, and the tools to derive, size and measure your own. Every figure names where it came from — and every figure we cannot establish says so.

OPEN DATA CC BY 4.0 · bulk JSON and CSV · redistributable under attribution

2,601 repositories indexed1,682 sized exactly0 fabricated scores

Independent model intelligence from LockedIn Labs

PINNED ARTIFACT MAP REGISTRY FACTS / V1.0.0
RROUTER
E01
E02
E03
E04
E05
E06
E07
E08
8 OF 128 EXPERTS ACTIVE / TOKEN
8 × H200 NODE VIEW1 GPU MIN. / CHECKPOINT ONLY
PINNED ARTIFACT61.1 GB
EXPERT ROUTING8 / 128
STATIC LOWER BOUND1 GPU MIN.

Qwen3-30B-A3B · sourced registry facts + calculated static fit · topology illustration, not measured runtime data

INDEX · EXACT ARTIFACTDERIVE · PINNED RECIPEMEASURE · OPEN HARNESSVERIFY · PORTABLE RECEIPT

ONE SYSTEM / MULTIPLE ENTRY POINTS

PLATFORM V0.1

Enter wherever the question starts.

The website is the visual workbench. The protocol, runner and developer surfaces make the same decision system portable.

THE DEPLOYMENT GAP

01 / 05

37B active does not mean 37B resident.

Sparse activation reduces compute. It does not erase model weights, KV cache, runtime buffers, replication, or all-to-all traffic.

MOEModels separates can load, can run, can scale, and makes economic sense— because they are four different answers.

01
FACTS

Every specification names the field or document it came from.

02
CALCULATIONS

Every derived value exposes its exact inputs and formula.

03
SILENCE

Every value the source does not establish is shown as unknown, with the reason.

THE ARTIFACT LAYER

02 / 05

A leaderboard ranks a name.
Deployment happens against an artifact.

The same model name spans a BF16 release, an FP8 release, a community requantisation and a fine-tune — different memory, different behaviour, different licence. Every record here is addressed by its commit.

Open the catalogue
2,601EXPERT-ROUTED REPOSITORIES
1,682SIZED FROM THE TENSOR INDEX
739PUBLISHERS
2026-09-05SNAPSHOT
01 Primary source

Moonshot AI

Kimi K3

A native multimodal 2.8T-class model for long-horizon coding, knowledge work, and million-token contexts.

TOTAL2.8T
ACTIVE104B
EXPERTS896
Long-horizon agentsView intelligence
02 Primary source

DeepSeek

DeepSeek V4 Pro

A frontier-scale model combining fine-grained sparse experts with a million-token context for agentic work.

TOTAL1.6T
ACTIVE49B
EXPERTS384
Frontier open reasoningView intelligence
03 Primary source

Z.ai

GLM-5.2

An open flagship designed for long engineering trajectories across a sourced million-token context.

TOTAL753B
ACTIVEUnknown
EXPERTS256
Long-horizon codingView intelligence
04 Primary source

Google

Gemma 4 26B A4B IT

A compact multimodal MoE with 25.2B total and 3.8B active parameters, designed for accessible inference.

TOTAL25.2B
ACTIVE3.8B
EXPERTS128
Single-accelerator baselineView intelligence

The four records above are the human-reviewed subset, sourced from pinned manifests, configurations, model cards and technical releases. The catalogue behind them is derived mechanically from publisher metadata and is labelled as such. Neither is a benchmark ranking.

MOE FIT CHECK

03 / 05

Turn an exact artifact into an honest lower bound.

Select a pinned checkpoint, hardware target, topology, and declared reserve. See what is proven—and what remains unknown.

Exact manifest bytes + integer math. No generated throughput, capacity, or price.

Deterministic registry engine

Will the checkpoint fit?

Test an exact, pinned artifact against advertised accelerator memory—then keep every unsupported conclusion visibly unknown.

Sourced + calculated

01 · Define baseline

Residency inputs

5 inputs
Total2.8T
Active / token104B
Artifact1.6 TB
GPUs per node

02 · Fit decision

Checkpoint cannot fit

Kimi K3 · 896 / top-16 experts · 1M context · 8 × NVIDIA H200 SXM · 13% reserve

Decision boundaryCheckpoint bytes only
01Baseline fails

Load

The checkpoint alone requires at least 13 GPUs at this reserve, before runtime allocations.

02Evidence required

Run

A baseline pass does not prove loader, kernel, quantization, sharding, or expert-parallel support.

03Unknown

Scale

No measured workload profile is attached, so throughput, latency, KV demand, and skew are not projected.

04Unknown

Economics

No dated provider, region, or utilization record is selected, so the engine emits no invented cost.

03 · Explainable topology

Requested

Pure integer math
Artifact
1.6 TBtensors
Reserve
Experts
Compute8 × H200
Checkpoint tensors
1.6 TB
exact manifest metadata
Usable / GPU
122.7 GB
after declared reserve
Device lower bound
13
before node rounding
Node-rounded
16 GPUs
2 × 8-GPU nodes

RequestedThe topology you asked the engine to test against the checkpoint baseline.

View calculation anatomy
Exact artifact tensor bytes
1,560,860,324,864
Advertised memory / GPU
141 GB
Declared reserve / GPU
18.3 GB
Usable memory / GPU
122.7 GB

usable = floor(advertised bytes × (10,000 − reserve bps) / 10,000); minimum GPUs = ceil(checkpoint tensor bytes / usable bytes). A failure is conclusive for this no-offload baseline; a pass is only a candidate for runtime validation.

Artifact evidence: Kimi K3 pinned tensor manifest ↗

SOURCED + CALCULATED · REGISTRY V1.0.0

Checkpoint residency is not full runtime residency. Validate loader support, memory use, topology, quality, latency, throughput, and cost on the intended system.

BENCHMARK EVIDENCE

04 / 05

A leaderboard should show its work.

Evidence is tiered, and every number carries its tier. Mechanically derived metadata covers thousands of artifacts. Reviewed claims keep scope, settings and missing context attached. No controlled run has crossed the comparison gate yet, and until one does this page says so.

Enter the evidence lab
EVIDENCE CLASSMETHODSTATUS
Hub-derived records2,601 repositoriesAVAILABLE
Owner reports15 sourced claimsAVAILABLE
Controlled endpoint runs0 admitted packsOPEN
Verified Deployment Passports0 admitted packsOPEN
Independent reproductions0 reproduced packsFUTURE
Calibrated configuration corpus0 configurationsFUTURE
DeployBench measures. Passport verifies the receipt.Admission and reproduction remain separate.

OPEN INFRASTRUCTURE

05 / 05

One engine.
Every interface.

Workbench, CLI, runner, REST API, TypeScript SDK and MCP server share the registry, evidence classes and deterministic planning contract.

moemodels / fitREGISTRY V1
$ npm run moemodels -- fit \
moonshotai/Kimi-K3 \
nvidia/h200-sxm-141gb \
--gpus 8 --reserve-pct 13
CHECKPOINTFAIL × 8
TOPOLOGY13 → 16
RUNTIMEUNKNOWN

Real offline CLI · same registry and integer engine as the hosted Fit Check

RESEARCH DESK

Read past the parameter count.

Read the methodology

FIELD GUIDE

Active parameters are not a deployment plan

A practical guide to resident weights, KV cache, runtime overhead, and the four different meanings of “fits.”

Grounded in the public methodology

SYSTEMS NOTE

Expert parallelism, without the hand-waving

How topology, all-to-all traffic, load imbalance, and hot experts reshape the economics of sparse inference.

Measured by DeployBench gates

BUYER BRIEF

Cloud endpoint or private cluster?

A decision framework for comparing utilization, privacy, operational burden, and three-year total cost.

Modeled in the workbench

START WITH THE PROOF

Break the receipt.
Watch trust fail closed.

Verify a deterministic Passport fixture, change exactly one byte, and see the content address reject it—all locally in your browser. This is the standard every measured number on this site has to meet.

Run the 90-second check