---
title: "SOTA models"
description: "The state-of-the-art model roster smithers configures: descriptions, badges, and role defaults. Registry v3, updated 2026-07-10."
---

{/* GENERATED FILE. Edit docs/data/sota-models.json, then run `pnpm sota:gen`. */}

**Registry v3** · updated **2026-07-10**. This page is generated from [`docs/data/sota-models.json`](https://github.com/smithersai/smithers/blob/main/docs/data/sota-models.json), the single source of truth for which models smithers configures by default. A daily research job checks every provider for new GA models and opens a PR here when the state of the art moves; `bunx smithers-orchestrator update` picks the changes up on your machine, and re-running `bunx smithers-orchestrator init` refreshes installed workflows to the new defaults.

## Badges

Each badge names the single best model for that job right now.

| Badge | Model | ID |
| --- | --- | --- |
| Best orchestrator | GPT-5.6 Sol | `gpt-5.6-sol` |
| Smartest reviewer | GPT-5.6 Sol | `gpt-5.6-sol` |
| Smartest coder | GPT-5.6 Sol | `gpt-5.6-sol` |
| Fast & cheap | GPT-5.6 Luna | `gpt-5.6-luna` |
| Best value coding | GPT-5.6 Luna | `gpt-5.6-luna` |
| Fastest coding | GPT-5.3-Codex-Spark | `gpt-5.3-codex-spark` |
| Best at UI | Gemini 3.5 Flash | `gemini-3.5-flash` |
| Best open source | Kimi K2.6 | `kimi-k2.6` |

## Role defaults

The Codex-first workflow tiers resolve to these ids; see [Recipes](/recipes) for practical workflow patterns:

| Role | Default model |
| --- | --- |
| orchestrator | `gpt-5.6-sol` |
| planning | `gpt-5.6-sol` |
| review | `gpt-5.6-sol` |
| smart | `gpt-5.6-sol` |
| midTier | `gpt-5.6-terra` |
| smartTool | `gpt-5.6-terra` |
| validate | `gpt-5.6-terra` |
| implement | `gpt-5.6-luna` |
| cheapFast | `gpt-5.6-luna` |
| ui | `gpt-5.6-luna` |
| realtime | `gpt-5.3-codex-spark` |
| research | `gpt-5.6-luna` |

### How to choose a tier

The role table is a starting policy, not a claim that every task belongs to one model. [OpenAI's GPT-5.6 release](https://openai.com/index/gpt-5-6/) describes a three-tier family: Sol is the flagship, Terra is balanced, and Luna is the fastest and most affordable. The release materials describe the family across software engineering, knowledge work, research, computer use, and tool use. In Smithers, that supports using Luna much more often than a narrow cheap-implementation-only policy, while still escalating when the decision warrants it.

| Situation | Start with | Escalate when |
| --- | --- | --- |
| Research, implementation, ordinary tool use, UI work, or routine-to-substantial execution | `gpt-5.6-luna` | The task is ambiguous, high-stakes, repeatedly failing, or needs a final frontier-level judgment |
| Explicit tool-heavy validation, structured checking, or higher-judgment mid-tier escalation | `gpt-5.6-terra` | The check itself requires difficult decomposition, novel judgment, or a final ship/no-ship decision |
| Orchestration, planning, final review, novel architecture, or the hardest reasoning | `gpt-5.6-sol` | Usually do not escalate further; use a human gate for decisions that require human authority |
| No usable Codex authentication for Sol-backed orchestration, planning, review, or smart work | `claude-fable-5` | Use the provider's supported fallback (Opus, then Kimi) or an explicit Claude-native specialist choice |
| No usable Codex authentication for Luna/Terra-backed research, implementation, validation, mid-tier, or tool-heavy work | `claude-sonnet-5` | Use the provider's supported fallback (Kimi) or an explicit Claude-native specialist choice |

Use Luna first, including ordinary tool use, then escalate deliberately: let Luna gather sources, edit code, use ordinary tools, and produce a substantive first result; use the `smartTool` role only when the work is explicitly tool-heavy and needs Terra's validation or higher judgment, and use Sol for planning and review when the decision warrants it. Agent arrays are sequential fallback chains: a later provider is attempted only when an earlier one is unavailable or fails. An explicitly constructed provider agent is a deliberate choice and can run even when Codex is healthy.

```tsx
const researcher = new CodexAgent({ model: "gpt-5.6-luna", config: { model_reasoning_effort: "medium" } });
const implementer = new CodexAgent({ model: "gpt-5.6-luna", config: { model_reasoning_effort: "medium" } });
const validator = new CodexAgent({ model: "gpt-5.6-terra" });
const reviewer = new CodexAgent({ model: "gpt-5.6-sol" });
const fableFallback = new ClaudeCodeAgent({ model: "claude-fable-5" });
const smartFallbackChain = [reviewer, fableFallback];
```

Fable 5 is not a Codex tier. Anthropic describes it as a model for ambitious, long, complex knowledge and coding work; developers can use `claude-fable-5` through the Claude API at $10 per million input tokens and $50 per million output tokens. Anthropic's July 1 redeployment restored access globally on Claude Platform, Claude.ai, Claude Code, and Claude Cowork. For Pro, Max, Team, and select Enterprise plans, Anthropic said Fable 5 would be included for up to 50% of weekly usage limits through July 12, 2026 at 11:59:59 PM PT ([promotion details](https://support.claude.com/en/articles/15424964-claude-fable-5-promotional-access)), after which use requires usage credits; standard Enterprise has no included allowance. Anthropic said it would re-enable AWS, Google Cloud, and Microsoft Foundry as quickly as possible, while its current Fable page lists availability through available marketplaces and those cloud platforms, so cloud-provider and account availability should be treated as conditional rather than universal. Its updated safeguards can reroute blocked requests to Opus 4.8 and can false-positive more often during routine coding and debugging. In current Claude applications and Claude Code behavior, that Fable-to-Opus switching is enabled by default, while API customers must opt in and configure the fallback themselves ([default product behavior and API opt-in](https://support.claude.com/en/articles/15363606-why-claude-switched-models-in-your-conversation-with-fable-5)). Treat this as current product behavior, not a permanent provider guarantee. Smithers therefore keeps Fable as a non-Codex fallback for Sol-backed smart, planning, review, and orchestration roles, or a deliberate Claude-native specialist when those cost, availability, and safeguard tradeoffs fit; Luna/Terra-backed research, implementation, validation, mid-tier, and tool-heavy roles fall back to Sonnet instead, not Fable; the cited sources do not establish a general latency comparison. Automatic fallback pools do not silently run Fable in parallel with a healthy Codex path; an explicit Claude/OpenCode workflow may choose it directly. In Claude Code the model id is `claude-fable-5`; the OpenCode configuration uses the provider-qualified id `anthropic/claude-fable-5`. See [Anthropic's Fable 5 announcement](https://www.anthropic.com/news/claude-fable-5-mythos-5) and [July redeployment update](https://www.anthropic.com/news/redeploying-fable-5).

## Anthropic

### Claude Fable 5 (`claude-fable-5`)

current · engines: `claude`, `opencode` · roles: orchestrator, planning, review, smart

Anthropic's Mythos-class model for ambitious, long, complex knowledge and coding work. Developers can use `claude-fable-5` through the Claude API at $10 per million input tokens and $50 per million output tokens. Anthropic's July 1 redeployment restored access on Claude Platform, Claude.ai, Claude Code, and Claude Cowork; the temporary included window for eligible subscription plans runs through July 12, 2026 at 11:59:59 PM PT ([promotion details](https://support.claude.com/en/articles/15424964-claude-fable-5-promotional-access)), and cloud-platform availability remains subject to the marketplace, provider, and account. Its updated safeguards may reroute blocked requests to Opus 4.8 and may false-positive during routine coding and debugging. Current Claude applications and Claude Code enable that switching by default, while API customers must opt in and configure it ([default product behavior and API opt-in](https://support.claude.com/en/articles/15363606-why-claude-switched-models-in-your-conversation-with-fable-5)); treat the notice as current product behavior rather than a permanent provider guarantee. Smithers uses Fable as a non-Codex fallback for Sol-backed smart, planning, review, and orchestration roles or as a deliberate Claude-native specialist. Claude Code uses `claude-fable-5`; Smithers' OpenCode configuration uses the provider-qualified id `anthropic/claude-fable-5`. See [Anthropic's launch announcement](https://www.anthropic.com/news/claude-fable-5-mythos-5), [redeployment update](https://www.anthropic.com/news/redeploying-fable-5), and [current Fable availability](https://www.anthropic.com/claude/fable).

### Claude Opus 4.8 (`claude-opus-4-8`)

current · engines: `claude`, `opencode` · roles: smart

Anthropic's Opus tier. Still a top-shelf generalist and the always-present fallback behind Fable in the smart, planning, and review pools.

### Claude Sonnet 5 (`claude-sonnet-5`)

current · released 2026-06-29 · engines: `claude`, `opencode` · roles: implement, cheapFast

The newest Sonnet: fast, cheap, 1M context. It is the primary non-Codex fallback for Luna/Terra-backed research, implementation, validation, mid-tier, and tool-heavy work when Codex is unavailable; Sol-backed orchestration, planning, review, and smart work fall back to Fable instead.

### Claude Haiku 4.5 (`claude-haiku-4-5`)

current · engines: `claude`, `opencode`

Anthropic's cheapest tier, for high-volume summarization and classification where even Sonnet is overkill.

## OpenAI

### GPT-5.6 Sol (`gpt-5.6-sol`)

**Best orchestrator** · **Smartest reviewer** · **Smartest coder** · state of the art · engines: `codex`, `pi` · roles: orchestrator, planning, review, smart

OpenAI's GPT-5.6 flagship for the hardest reasoning, coding, and judgment-heavy work. Keep Sol for orchestration, planning, final review, ambiguous or high-stakes decisions, and recovery when a lower-cost pass is not enough; do not spend it on routine implementation by default. See [OpenAI's GPT-5.6 release](https://openai.com/index/gpt-5-6/).

### GPT-5.6 Terra (`gpt-5.6-terra`)

state of the art · engines: `codex`, `pi` · roles: midTier, smartTool, validate

OpenAI's balanced GPT-5.6 model for validation and higher-judgment, explicitly tool-heavy work. Terra is the `smartTool` escalation when a routine Luna pass needs more checking or consistency but the task does not need Sol's top-tier planning and review; ordinary tool use starts with Luna. See [OpenAI's GPT-5.6 release](https://openai.com/index/gpt-5-6/).

### GPT-5.6 Luna (`gpt-5.6-luna`)

**Fast & cheap** · **Best value coding** · state of the art · engines: `codex`, `pi` · roles: implement, cheapFast, research, ui

OpenAI's fastest and most affordable GPT-5.6 tier, with strong capability across the family’s software, knowledge-work, research, computer-use, and tool-using workloads. Ordinary tool use starts with Luna, which is the default for research, implementation, routine-to-substantial execution, UI work, cheapFast tasks, and the first pass on many tasks that do not require Sol's judgment. Escalate to Terra only for explicit tool-heavy validation or higher-judgment checking; escalate to Sol for ambiguity, high stakes, repeated failure, or unusually long-horizon reasoning rather than assuming task size alone requires Sol. See [OpenAI's GPT-5.6 release](https://openai.com/index/gpt-5-6/) and the [GPT-5.6 preview release](https://openai.com/index/previewing-gpt-5-6-sol/).

### GPT-5.5 (`gpt-5.5`)

current · engines: `codex`, `pi`

The previous OpenAI flagship. Keep it as a compatibility fallback for Codex accounts that do not yet expose GPT-5.6.

### GPT-5.4 (`gpt-5.4`)

current · engines: `codex`, `pi`

The previous OpenAI flagship, retained for pinned compatibility. New Smithers workflows use the GPT-5.6 Sol/Terra/Luna role split instead.

### GPT-5.4 mini (`gpt-5.4-mini`)

current · engines: `codex`, `pi`

OpenAI's prior fast, efficient tier. Retained as the OpenRouter compatibility fallback (openai/gpt-5.4-mini); Codex-native cheap work defaults to GPT-5.6 Luna.

### GPT-5.3-Codex-Spark (`gpt-5.3-codex-spark`)

**Fastest coding** · state of the art · released 2026-02-12 · engines: `codex` · roles: realtime

OpenAI's first real-time coding model: 1000+ tokens per second on dedicated Cerebras hardware while staying genuinely capable. Research preview, ChatGPT Pro only. Reach for it when iteration latency matters more than depth.

## Google

### Gemini 3.5 Flash (`gemini-3.5-flash`)

**Best at UI** · state of the art · released 2026-05-19 · engines: `antigravity` · roles: ui, implement, cheapFast

Google's best price-to-performance model and the best non-Codex fallback for UI work: near-Pro intelligence at Flash speed and cost, 1M context, and it beats Gemini 3.1 Pro on coding and agentic benchmarks while running roughly 4x faster. Smithers can use it for UI work when its provider-specific route is configured; it is not a universal fallback policy.

### Gemini 3.1 Pro (`gemini-3.1-pro-preview`)

current · engines: `antigravity`

Google's Pro tier (still preview). Superseded for coding and agentic work by Gemini 3.5 Flash; keep it for long-horizon reasoning where Pro depth wins.

### Gemini 3.1 Flash-Lite (`gemini-3.1-flash-lite`)

current · engines: `antigravity`

Frontier-class performance at a fraction of the cost. The floor of the Gemini lineup for bulk, low-stakes calls.

## Moonshot AI

### Kimi K2.7-Code (`kimi-k2.7-code`)

state of the art · released 2026-06-12 · engines: `kimi` · roles: implement, cheapFast

Moonshot's most capable coding model: 256k context, roughly 30% fewer reasoning tokens than K2.6, and strong instruction-following in long contexts. Smithers keeps it as a no-Codex implementation fallback; the -highspeed variant trades a little quality for ~180 tok/s.

### Kimi K2.7-Code High-Speed (`kimi-k2.7-code-highspeed`)

current · engines: `kimi` · roles: realtime

The high-throughput K2.7-Code variant, around 180 tokens per second. The open-weights answer to Codex-Spark for latency-sensitive loops.

### Kimi K2.6 (`kimi-k2.6`)

**Best open source** · current · released 2026-04-20 · engines: `kimi` · roles: research

Moonshot's open-source (modified MIT) trillion-parameter MoE flagship: native multimodal, agent swarms up to 300 sub-agents, up to 13 hours of continuous coding. Ties GPT-5.5 on SWE-Bench Pro at roughly 80% lower cost. The strongest model you can self-host.

## Benchmarks

Independent of the roster above: how these models actually score. smithers ships two benchmark harnesses in-repo: [`benchmarks/roadmapbench`](https://github.com/smithersai/smithers/tree/main/benchmarks/roadmapbench) (RoadmapBench, a real audited run) and [`benchmarks/site`](https://github.com/smithersai/smithers/tree/main/benchmarks/site) (the benchmarks.smithers.sh leaderboard, sourced from `benchmarks/results.json`). Only results for models that still appear in the registry above are shown; rows for older models (e.g. Claude Opus 4.6, GPT-5.2) are dropped automatically. `pending` rows are honest placeholders: the smithers fleet run has not completed at full scale yet.

{/* Generated from docs/data/sota-benchmarks.json. Rows naming a deprecated or unlisted model are filtered out. */}

### RoadmapBench

[UniPat-AI/RoadmapBench (115 tasks)](https://github.com/UniPat-AI/RoadmapBench) · metric: Resolved Rate (RR) · Completion Score (CS) · harness: `benchmarks/roadmapbench`

Long-horizon, multi-target version upgrades: start from a repo pinned to an old release and implement every independent feature a real upstream bump introduced (median oracle change ~3,700 LOC across ~51 files; median 5 scored targets). The best single agent on the official leaderboard resolves under 40% of tasks.

| Models | Harness | Score | Sample | Notes |
| --- | --- | --- | --- | --- |
| Claude Opus 4.8 + GPT-5.5 | smithers (fable-sandwich) | **RR 0.50 · CS 0.857** | curated subset (Python + TypeScript) · n=2 | every grader fair-validated (oracle=1.0, no-op<1.0); every run audited untainted. Not a full-115 claim. |
| public SOTA (best single agent) | official | RR ~0.39 · CS ~0.69 | full-115 · n=115 | approximate published best on the official leaderboard |

### SWE-Bench Pro

[ScaleAI/SWE-bench_Pro (test, 731 tasks)](https://github.com/scaleapi/SWE-bench_Pro-os) · metric: Pass@1 (%) · harness: `benchmarks/site`

731 multi-file tasks across 11 professional repos (Go/Python/JS/TS) graded by hidden tests in canonical per-instance Docker. Moonshot reports Kimi K2.6 tying GPT-5.5 here at roughly 80% lower cost.

| Models | Harness | Score | Sample | Notes |
| --- | --- | --- | --- | --- |
| Claude Opus 4.8 + Claude Sonnet 5 | smithers (delegation-chain) | pending | full-731 | Claude-only fleet run pending |

### Claw-Eval-Live

[Claw-Eval-Live (105 tasks / 17 families)](https://arxiv.org/abs/2604.28139) · metric: Score (pass bar 75) · harness: `benchmarks/site`

Agentic enterprise workflows scored on observable execution evidence. No public model clears the 70% pass bar; frontier flagships cluster in the low 80s.

| Models | Harness | Score | Sample | Notes |
| --- | --- | --- | --- | --- |
| GPT-5.4 | official | 81.7 | full-105 · n=105 | public leaderboard |
| smithers (mixture) | mixture-gateway | pending | pending | cannot run faithfully Claude-only (native OpenAI gather leg + neutral Gemini judge); asterisked variant only |

### SWE-EVO

[SWE-EVO (48 release-sized tasks / 7 repos)](https://arxiv.org/abs/2512.18470) · metric: Resolved Rate (%) · harness: `benchmarks/site`

Carry a Python project across a whole release transition. Frontier agents resolve only ~21-25% of the full-48 set.

| Models | Harness | Score | Sample | Notes |
| --- | --- | --- | --- | --- |
| GPT-5.4 | official (OpenHands) | 25.0 | full-48 · n=48 | Wilson 95% CI [14.9, 38.8] |
| Claude Opus 4.8 + Claude Sonnet 5 | smithers (delegation-chain) | pending | dvc subset | Claude-only fleet run pending; dvc subset is easier than full-48, not directly comparable |

## Deprecated ids

Rewrite these on sight; the daily research job does the same sweep mechanically.

| Deprecated | Use instead |
| --- | --- |
| `claude-sonnet-4-6` | `claude-sonnet-5` |
| `claude-sonnet-4-7` | `claude-sonnet-5` |
| `claude-sonnet-4-20250514` | `claude-sonnet-5` |
| `gpt-5.3-codex` | `gpt-5.6-luna` |
| `gpt-5.2` | `gpt-5.6-luna` |
| `gpt-4o` | `gpt-5.4-mini` |
| `kimi-latest` | `kimi-k2.7-code` |

## Update policy

- Only models with exact usable ids confirmed by provider documentation enter the default registry; marketing-only names and previews without usable ids wait.
- Research previews with real availability (e.g. gpt-5.3-codex-spark on ChatGPT Pro) may enter with status sota for their niche, noted in the description.
- No floating aliases (kimi-latest, *-latest). Pin concrete ids so a provider-side model swap cannot bypass this registry.
- Every badge names exactly one model. A new badge holder demotes the old one in the same change.
- Any change to models bumps version by exactly 1 and refreshes updatedAt.
- Deprecated entries keep their replacedBy id for one release so sweeps know what to rewrite, then get deleted.
