Claude Fable 5 is a Mythos-class model from Anthropic, built for autonomous knowledge work and coding. It supports text, image, and file inputs with text output, with reasoning support and...
Cele mai bune API-uri de modele de cod pentru agenti si code review
Compara API-uri de modele orientate pe cod dupa context, suport tool, output JSON, latenta, pret si rol recomandat in productie.
La ce folosește această listă scurtă?: Modele de cod
Selectia unui model de cod depinde de dimensiunea repository-ului, nevoile de tool calling, fiabilitatea instructiunilor si costul outputului lung. Un asistent care citeste un codebase mare are nevoie de o economie diferita fata de o functie simpla de completare. NextModel evidentiaza contextul, suportul tool, pretul si ghidajul de folosire pentru a ajuta echipele sa aleaga un model principal si o politica de fallback.
Baza sursei: Taxonomia use case NextModel si metadatele OpenRouter pentru parametrii suportati, cand sunt disponibile. · Actualizat 2026-07-01
Fit score
Candidați recomandați modele de cod
Pornește de la lista scurtă, testează prompturi reale și compară costul lunar înainte de routingul de producție.
Claude Haiku 4.5 is Anthropic’s fastest and most efficient model, delivering near-frontier intelligence at a fraction of the cost and latency of larger Claude models. Matching Claude Sonnet 4’s performance...
Claude Opus 4.5 is Anthropic’s frontier reasoning model optimized for complex software engineering, agentic workflows, and long-horizon computer use. It offers strong multimodal capabilities, competitive performance across real-world coding and...
Opus 4.6 is Anthropic’s strongest model for coding and long-running professional tasks. It is built for agents that operate across entire workflows rather than single prompts, making it especially effective...
Tabel comparativ
Compară lista scurtă după preț, furnizor, context, capacități și sursă.
Folosește această vedere când restrângi o shortlist de producție, construiești o politică de fallback sau compari economia modelelor.
| Model | Provider | Input | Output | Context | Capabilities | Best for | Latency | Status | Source |
|---|---|---|---|---|---|---|---|---|---|
| Anthropic: Claude Fable 5anthropic/claude-fable-5 | Anthropic | $1.45 / 1M tokens | $7.23 / 1M tokens | 1M | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated |
| Anthropic: Claude Haiku 4.5anthropic/claude-haiku-4.5 | Anthropic | $0.145 / 1M tokens | $0.723 / 1M tokens | 200k | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated |
| Anthropic: Claude Opus 4.5anthropic/claude-opus-4.5 | Anthropic | $0.723 / 1M tokens | $3.62 / 1M tokens | 200k | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated |
| Anthropic: Claude Opus 4.6anthropic/claude-opus-4.6 | Anthropic | $0.723 / 1M tokens | $3.62 / 1M tokens | 1M | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated |
| Anthropic: Claude Opus 4.7anthropic/claude-opus-4.7 | Anthropic | $0.723 / 1M tokens | $3.62 / 1M tokens | 1M | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated |
| Anthropic: Claude Opus 4.8anthropic/claude-opus-4.8 | Anthropic | $0.723 / 1M tokens | $3.62 / 1M tokens | 1M | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated |
| Claude Opus 5anthropic/claude-opus-5 | Anthropic | $0.723 / 1M tokens | $3.62 / 1M tokens | 1M | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated |
| Anthropic: Claude Sonnet 4.5anthropic/claude-sonnet-4.5 | Anthropic | $0.434 / 1M tokens | $2.17 / 1M tokens | 1M | StreamingTool callingJSON modeVision | image understanding, multimodal chat | 1000-3000ms | Catalog | Platform curated |
FAQ
Modele de cod FAQ
Ce face un model bun pentru agentii de cod?
Contextul lung, tool calling-ul fiabil, outputul structurat si urmarirea stabila a instructiunilor conteaza mai mult decat pretul brut pe token.
Cum ar trebui controlat costul agentilor de cod?
Foloseste politici de buget, compara costul outputului lung si ruteaza sarcinile simple catre modele mai ieftine inainte sa escalezi cazurile dificile.
Clasamente