> ## Documentation Index
> Fetch the complete documentation index at: https://smithers.sh/llms.txt
> Use this file to discover all available pages before exploring further.

# SOTA models

> The state-of-the-art model roster smithers configures: descriptions, badges, and role defaults. Registry v1, updated 2026-07-06.

**Registry v1** · updated **2026-07-06**. 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 | Claude Fable 5      | `claude-fable-5`      |
| Smartest reviewer | Claude Fable 5      | `claude-fable-5`      |
| Smartest coder    | Claude Fable 5      | `claude-fable-5`      |
| Fastest coding    | GPT-5.3-Codex-Spark | `gpt-5.3-codex-spark` |
| Best at UI        | Gemini 3.5 Flash    | `gemini-3.5-flash`    |
| Fast & cheap      | Gemini 3.5 Flash    | `gemini-3.5-flash`    |
| Best value coding | Kimi K2.7-Code      | `kimi-k2.7-code`      |
| Best open source  | Kimi K2.6           | `kimi-k2.6`           |

## Role defaults

The fable-sandwich tiers (see the [workflow optimization guide](/guides/workflow-optimization)) resolve to these ids:

| Role         | Default model         |
| ------------ | --------------------- |
| orchestrator | `claude-fable-5`      |
| planning     | `claude-fable-5`      |
| review       | `claude-fable-5`      |
| smart        | `claude-fable-5`      |
| implement    | `gpt-5.5`             |
| cheapFast    | `gemini-3.5-flash`    |
| ui           | `gemini-3.5-flash`    |
| realtime     | `gpt-5.3-codex-spark` |
| research     | `kimi-k2.6`           |

## Anthropic

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

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

Anthropic's Mythos-class frontier model, the first of the Claude 5 family. The strongest model available for planning, code review, and orchestrating other agents, which is why it sits at both ends of the fable sandwich: it writes the plan, delegates implementation, then reviews the result.

### 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. The guaranteed implementer fallback in the fable sandwich and the default cheapFast Claude.

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

state of the art · engines: `codex`, `pi` · roles: implement, smart

OpenAI's GA flagship and the Codex CLI default. The implementation workhorse in the middle of the fable sandwich. With ChatGPT auth use the id gpt-5.5 exactly (gpt-5.5-codex and gpt-5.3-codex are deprecated in Codex).

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

current · engines: `codex`, `pi`

The previous OpenAI flagship. Still solid for professional work when gpt-5.5 quota is tight.

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

current · engines: `codex`, `pi` · roles: cheapFast

OpenAI's fast, efficient tier. The default cheap OpenAI model, including via OpenRouter (openai/gpt-5.4-mini).

### 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** · **Fast & cheap** · state of the art · released 2026-05-19 · engines: `antigravity` · roles: ui, implement, cheapFast

Google's best price-to-performance model and the best model 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. The default Gemini in smithers.

### 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`)

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

Moonshot's most capable coding model and the best coding value on the market: 256k context, roughly 30% fewer reasoning tokens than K2.6, strong instruction-following in long contexts. The default Kimi in smithers; 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.

## 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-5.5`         |
| `gpt-5.2`                  | `gpt-5.5`         |
| `gpt-4o`                   | `gpt-5.4-mini`    |
| `kimi-latest`              | `kimi-k2.7-code`  |

## Update policy

* Only GA (generally available) models enter the registry. Limited previews (e.g. GPT-5.6 Sol/Terra/Luna) wait until they ship for real.
* 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.