Comparez les API orientees code par longueur de contexte, support des outils, sortie JSON, latence, prix et role recommande en production.
Le choix d'un modele de code depend de la taille du depot, des besoins en tool calling, de la fiabilite des instructions et du cout des sorties longues. Un assistant qui lit un grand codebase n'a pas la meme economie qu'une simple completion courte. NextModel met en regard contexte, support des outils, prix et usage recommande afin que les equipes choisissent un modele principal puis une politique de repli.
Base de source: Taxonomie d'usages NextModel et metadonnees de parametres supportes OpenRouter quand elles sont disponibles. · Mis a jour 2026-07-01
Fit score
Commencez par cette selection, puis testez de vrais prompts et comparez le cout mensuel avant le routage de production.
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...
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...
Tableau comparatif
Utilisez cette vue pour reduire une shortlist de production, construire une politique de repli ou comparer l'economie des modeles.
| 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
Un long contexte, un tool calling fiable, une sortie structuree et une bonne discipline d'instruction comptent davantage que le seul prix du token.
Utilisez des politiques de budget, comparez le cout des sorties longues et routez les taches simples vers des modeles moins chers avant d'escalader les cas difficiles.
Classements