{"id":2098,"date":"2026-08-03T18:32:01","date_gmt":"2026-08-03T18:32:01","guid":{"rendered":"https:\/\/convly.ai\/claude-api-pricing\/"},"modified":"2026-08-03T18:32:01","modified_gmt":"2026-08-03T18:32:01","slug":"claude-api-pricing","status":"publish","type":"page","link":"https:\/\/convly.ai\/fr\/claude-api-pricing\/","title":{"rendered":"Tarification de l\u2019API Claude (2026) : co\u00fbt par million de jetons pour chaque mod\u00e8le"},"content":{"rendered":"

Claude API pricing runs from $1 per 1M input tokens on Claude Haiku 4.5 up to $10
\non Claude Fable 5.<\/strong> Anthropic bills input and output separately, and output costs five
\ntimes input across the entire range \u2014 so the headline input price tells you very little about
\nwhat you will actually pay. The table below gives every current model, and the blended column
\nis the number worth comparing.<\/p>\n

\n

Claude API pricing: every model, per 1M tokens<\/h2>\n \n \n \n \n \n \n \n \n \n
Model<\/th>Input $\/1M<\/th>Output $\/1M<\/th>\n Blended $\/1M<\/th>Context<\/th>\n <\/tr><\/thead>\n
Claude Haiku 4.5<\/a><\/td>\n $1.00<\/td>\n $5.00<\/td>\n $1.80<\/strong><\/td>\n 200K<\/td>\n <\/tr>\n
Claude Sonnet 5<\/a><\/td>\n $2.00<\/td>\n $10.00<\/td>\n $3.60<\/strong><\/td>\n 1M<\/td>\n <\/tr>\n
Claude Sonnet 4.6<\/a><\/td>\n $3.00<\/td>\n $15.00<\/td>\n $5.40<\/strong><\/td>\n 1M<\/td>\n <\/tr>\n
Claude Opus 5<\/a><\/td>\n $5.00<\/td>\n $25.00<\/td>\n $9.00<\/strong><\/td>\n 1M<\/td>\n <\/tr>\n
Claude Opus 4.8<\/a><\/td>\n $5.00<\/td>\n $25.00<\/td>\n $9.00<\/strong><\/td>\n 1M<\/td>\n <\/tr>\n
Claude Fable 5<\/a><\/td>\n $10.00<\/td>\n $50.00<\/td>\n $18.00<\/strong><\/td>\n 1M<\/td>\n <\/tr>\n <\/tbody>\n <\/table>\n

Blended is the effective rate at a 4:1 input-to-output mix, which is what a\n typical chat or retrieval workload actually produces. It is the number to compare across\n vendors \u2014 a headline input price hides how much the output side costs.<\/p>\n\n

What Claude costs per month<\/h2>\n \n \n \n \n \n
Workload<\/th>Tokens \/ month<\/th>\n Claude Haiku 4.5
cheapest<\/span><\/th>\n 		Claude Fable 5
most capable tier<\/span><\/th>\n <\/tr><\/thead>\n
Side project<\/td>\n 1M in \/ 0.25M out<\/td>\n $2.25<\/strong><\/td>\n $23<\/strong><\/td>\n <\/tr>\n
Small team<\/td>\n 20M in \/ 5M out<\/td>\n $45<\/strong><\/td>\n $450<\/strong><\/td>\n <\/tr>\n
Production<\/td>\n 200M in \/ 50M out<\/td>\n $450<\/strong><\/td>\n $4,500<\/strong><\/td>\n <\/tr>\n <\/tbody>\n <\/table>\n

Model your own volumes in the\n AI API cost calculator<\/a>.<\/p>\n\n

How Claude compares to other providers<\/h2>\n

Each provider's cheapest priced model, so the comparison is like for like on entry cost.<\/p>\n \n \n \n \n \n \n \n \n \n \n \n \n \n
Provider<\/th>Cheapest model<\/th>Blended $\/1M<\/th><\/tr><\/thead>\n
Mistral AI<\/td>\n Mistral 7B<\/a><\/td>\n $0.0220<\/td>\n <\/tr>\n
Meta<\/td>\n Llama 3.1 8B<\/a><\/td>\n $0.0220<\/td>\n <\/tr>\n
Alibaba<\/td>\n Qwen3 8B<\/a><\/td>\n $0.0600<\/td>\n <\/tr>\n
Google<\/td>\n Gemma 3 4B<\/a><\/td>\n $0.0600<\/td>\n <\/tr>\n
Microsoft<\/td>\n Phi-4<\/a><\/td>\n $0.0840<\/td>\n <\/tr>\n
DeepSeek<\/td>\n DeepSeek V4-Flash<\/a><\/td>\n $0.168<\/td>\n <\/tr>\n
Moonshot AI<\/td>\n Kimi K2.7 Code<\/a><\/td>\n $0.980<\/td>\n <\/tr>\n
Anthropic this page<\/span><\/td>\n Claude Haiku 4.5<\/a><\/td>\n $1.80<\/td>\n <\/tr>\n
Zhipu AI<\/td>\n GLM 5.2<\/a><\/td>\n $2.00<\/td>\n <\/tr>\n
xAI<\/td>\n Grok 4<\/a><\/td>\n $5.40<\/td>\n <\/tr>\n
OpenAI<\/td>\n GPT-5.6 Sol<\/a><\/td>\n $10.00<\/td>\n <\/tr>\n <\/tbody>\n <\/table>\n

Cheapest is not the same as best value \u2014 check capability alongside price on the\n LLM leaderboard<\/a>, or browse every\n model in the AI models database<\/a>.<\/p>\n <\/div>\n\n

Which Claude model should you use?<\/h2>\n

Anthropic’s line is a straightforward capability ladder, and most teams overpay by starting
\nat the top of it.<\/p>\n

Haiku 4.5<\/strong> is the one to treat as the default rather than the fallback. At
\n$1 in \/ $5 out it absorbs an order of magnitude more traffic than an Opus-tier model for the
\nsame money, and the vast majority of what a production application does \u2014 classification,
\nextraction, routing, short-form generation \u2014 never needed a frontier model. Its 200K context
\nis the one real limit; the rest of the line reaches 1M.<\/p>\n

Sonnet 5<\/strong> is the workhorse. Its benchmark profile is coding-heavy: 85.2% on
\nSWE-Bench Verified, 80.4% on Terminal-Bench 2.1, 81.2% on OSWorld-Verified. Those numbers sit
\nclose to models costing several times more, which is the whole argument for putting Sonnet
\nrather than Opus at the centre of a coding agent.<\/p>\n

Opus 5<\/strong> is the flagship, ranked first on the Artificial Analysis Intelligence
\nIndex at 61. It arrived at unchanged Opus pricing, so anyone already on Opus 4.8 can migrate
\nwith a model-string change and no budget consequence \u2014 worth doing promptly, because a
\ngenerational capability jump at flat pricing is rare.<\/p>\n

Fable 5<\/strong> only makes sense at the top of the difficulty curve. At $50 per 1M
\noutput tokens it costs roughly five times Opus on the output side, so routing ordinary requests
\nto it burns budget for no measurable gain. Reserve it for work where a wrong answer is
\nexpensive: unattended multi-step agents, deep research, refactors across a large codebase.<\/p>\n

The pattern that works is a router \u2014 Haiku in front, escalating to Sonnet or Opus only when
\na confidence check fails. Teams that instrument their token mix usually discover output is
\nwhere the bill actually lives, and that capping max_tokens<\/code> and moving first drafts
\nto a cheaper tier saves more than any prompt-compression trick.<\/p>\n

Three things about Claude pricing that catch people out<\/h2>\n

Sonnet 5’s price is temporary.<\/strong> The $2 \/ $10 rate is introductory and runs
\nthrough 31 August 2026, after which standard pricing of $3 \/ $15 applies. That is a 50%
\nincrease, and it will land silently on any workload sized against the current number. If you
\nare modelling unit economics for something launching this year, model it at $3 \/ $15 and treat
\ntoday’s rate as a discount.<\/p>\n

Opus 5’s Fast mode doubles both rates.<\/strong> The API-only Fast tier bills at
\n$10 \/ $50 rather than $5 \/ $25. It earns that only where latency is the product \u2014 interactive
\ncoding assistants, live agent loops where a user is waiting. For batch work, overnight agents
\nand anything queued, standard mode delivers the same intelligence at half the price.<\/p>\n

There is no long-context premium.<\/strong> This is the quiet advantage over rivals.
\nClaude Opus 4.8 bills its 1M-token context at the same rate from the first token to the
\nmillionth. Several competing models step the input rate up once a prompt passes a threshold \u2014
\nGPT-5.6 Sol charges 2x input and 1.5x output above 272K tokens, and Gemini 3.1 Pro roughly
\ndoubles input above 200K. That makes their long-context features unpredictable to budget,
\nbecause the same feature costs a different amount depending on how much a user pasted in. With
\nClaude you can size prompts around what produces the best answer rather than around a pricing
\ncliff.<\/p>\n

\n

Frequently asked questions<\/h2>\n
\n
How much does the Claude API cost?<\/summary>

Claude API pricing runs from $1.80 per 1M blended tokens on Claude Haiku 4.5 up to $18.00 on Claude Fable 5. Blended assumes a 4:1 input-to-output mix. Input and output are billed separately, and output is always the more expensive side.<\/p><\/details>\n

What is the cheapest Claude model?<\/summary>

Claude Haiku 4.5, at $1.00 per 1M input tokens and $5.00 per 1M output. A small-team workload of 20M input and 5M output tokens a month costs about $45 on it.<\/p><\/details>\n

How much does Claude cost per month?<\/summary>

At 20M input and 5M output tokens a month, Claude Haiku 4.5 costs about $45 and Claude Fable 5 about $450. A side project at 1M\/0.25M costs a small fraction of that. Use the AI API cost calculator for your own volumes.<\/p><\/details>\n

Is Claude cheaper than Mistral AI?<\/summary>

On entry-level pricing, Claude starts at $1.80 per 1M blended and Mistral AI starts at $0.0220 on Mistral 7B. Mistral AI is the cheaper entry point, though capability differs \u2014 compare both on the leaderboard before switching.<\/p><\/details>\n

Why does Claude charge more for output tokens than input?<\/summary>

Output tokens are generated one at a time and cannot be batched the way a prompt can, so they cost more to serve. This is why prompt-heavy workloads such as retrieval and classification are far cheaper to run than generation-heavy ones, and why the blended rate matters more than the headline input price.<\/p><\/details>\n <\/div>\n

Prices are the published list rates for each model's primary API and are reviewed as\n providers change them. Volume, batch and cached-input discounts are not included. Last reviewed\n August 2026.<\/p>\n<\/div>\n\n