MODELS / YOUR INTELLIGENCE, YOUR CHOICE
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Build your model team with theo’s built-in MCIR memory carrying relevant context across requests. Compare published evidence and meet our first-party models. Real names. Sourced scores. Availability kept explicit.
Big model energy.The names you know. The choice is yours.
OpenAI
Claude
Gemini
DeepSeek
theo Arca
Grok
Kimi
Qwen
Meta
Mistral
theo Moonlight
GLM
MiniMax
NVIDIA
Kling
Runway
FLUX
PikaBrands in the directory, not a guarantee of account availability or local installation. No partnership or endorsement implied.
Model catalog and benchmark comparison
Our own models. Ready to use.
Live in the products shown below.
Being available is different from having a benchmark score.
TextTheoArca Magnus 5.1
Theo's own deep-reasoning engine, governed and audited.
Context window1,000,000 tokensPublisher-reported · Sep 3, 2026
The whole conversation, documents included, in one request. This is not an independent benchmark.
TextTheoArca Velox 5.1
Theo's own low-latency engine, governed and audited.
Context window1,000,000 tokensPublisher-reported · Sep 3, 2026
The whole conversation, documents included, in one request. This is not an independent benchmark.
ImageTheo Moonlight 1.1
High fidelity image renders on our own hardware.
Render time33 secondsPublisher-reported · Sep 15, 2026
A 1024 by 1024 image at the default quality setting. This is not an independent benchmark.
3D captureTheo Real World 1.1
Photos of a real thing become a 3D capture of the thing in its space.
Quick capture127 secondsPublisher-reported · Sep 21, 2026
From submit, on a 9 second walk-around clip; 40 camera positions solved from 120 candidate frames. This is not an independent benchmark.
A little less hype.
A lot more evidence.
Score snapshot Catalog checked . Not a live availability list.
1–12 of 169 models
Ranked models first. Overlapping bands are ties.Swipe or scroll the table to see scores, evidence, and sources.
| Overall rank | Model | Overall Index | Index grade | Coverage & evidence | Source |
|---|---|---|---|---|---|
| 1band 1–1 | GPT-6 AstraOpenAI · Text | 99.0band 99.0–99.7 | A+ | Independent / public boards14 comparable tests · 3 counting categoriesEpoch 5 · boards 9 | Source |
| 2band 2–2 | Claude Fable 5.1Anthropic · Text | 97.0band 96.6–97.8 | A+ | Independent / public boards17 comparable tests · 3 counting categoriesEpoch 4 · boards 13 | Source |
| 3band 3–4 | Claude Fable 5Anthropic · Text | 92.7band 91.9–95.6 | A | Independent / public boards19 comparable tests · 3 counting categoriesEpoch 5 · boards 14 | Source |
| 4band 3–4 | Claude Opus 5Anthropic · Text | 92.6band 91.7–94.3 | A | Independent / public boards20 comparable tests · 3 counting categoriesEpoch 5 · boards 15 | Source |
| 5band 5–5 | GPT-5.6 SolOpenAI · Text | 89.8band 88.7–92.4 | A- | Independent / public boards20 comparable tests · 3 counting categoriesEpoch 5 · boards 15 | Source |
| 6band 6–6 | GPT-5.6 TerraOpenAI · Text | 81.9band 80.2–85.3 | B+ | Independent / public boards18 comparable tests · 3 counting categoriesEpoch 5 · boards 13 | Source |
| 7band 6–9 | GPT-5.5OpenAI · Text | 80.2band 78.8–82.8 | B+ | Independent / public boards22 comparable tests · 4 counting categoriesEpoch 5 · boards 17 | Source |
| 8band 6–10 | Kimi K3Moonshot AI · Text Open weights | 79.6band 77.2–83.5 | B | Independent / public boards18 comparable tests · 3 counting categoriesEpoch 5 · boards 13 | Source |
| 9band 7–9 | Claude Opus 4.8Anthropic · Text | 79.5band 77.7–81.8 | B | Independent / public boards21 comparable tests · 4 counting categoriesEpoch 5 · boards 16 | Source |
| 10band 10–11 | GPT-5.4OpenAI · Text | 77.3band 75.2–79.1 | B | Independent / public boards21 comparable tests · 4 counting categoriesEpoch 6 · boards 15 | Source |
| 11band 10–16 | Claude Opus 4.6Anthropic · Text | 75.4band 72.6–78.4 | B | Includes developer reports22 comparable tests · 4 counting categoriesEpoch 6 · boards 15 · developer-reported 1 | Source |
| 12band 9–16 | Gemini 3.7 FlashGoogle · Text | 75.2band 71.9–79.5 | B | Independent / public boards14 comparable tests · 3 counting categoriesEpoch 5 · boards 9 | Source |
How to read the rankings, sources, and availability
A relative Index, not an accuracy percentage. OpenCharts balances performance across counting categories, relative to the published frontier. An overall rank needs at least six comparable tests across three counting categories. Provisional scores do not meet that threshold. Missing scores stay missing.
Read the bands, not just the position. Overlapping rank bands should be treated as ties. Changing the category or hard-set sort never changes a model’s published overall rank. Category means with limited coverage are labelled; the hard-set score requires at least four covered tests.
Different evidence stays different. Epoch runs, public leaderboards, developer reports, and internal evaluations are counted separately. A developer report is not an independent evaluation. First-party observations above are publisher-reported. Image, video, voice, presenter, and 3D capture entries are not assigned a text-model Index.
A directory is not an availability API. A listing, logo, or open-weight flag does not guarantee hitheo access, a public API, or local compatibility. Check the source, your account, hardware requirements, and the model’s license before use.
Product availability has its own source. The first-party live labels reflect a product team confirmation on . They name the product where each model is live. Benchmark scores, publisher measurements, and public-API distribution remain separate records from OpenCharts.
Benchmark snapshot: . Internal evaluation snapshot: . First-party feed checked: . Media names reviewed: .
Aggregates reproduced from OpenCharts. Underlying score sources include Epoch AI and Arena, licensed CC BY 4.0. This is a reduced, regrouped projection; published scores and rank bands are unchanged. The source records retain test-level attribution and conditions.
Try routing and local setupCapability examples, separate from the comparison catalog.
Choose a capability and make it part of your orchestrator.
Start with auto. Supported memory paths can bring relevant context to the chosen route.
Install compatible local models. Review the choice before downloading.
Find your kind of intelligence.
16 examples in this preview
Public theo capabilities and local setup examples, not a live account inventory. Cloud models are not automatically available to run locally.