What is the best LLM API in 2026?

The Claude API is our first pick when the model has to plan, write code or chain tool calls. There are four tiers. Haiku 5.5 costs $0.10 per million input tokens and $0.50 per million output, as long as the prompt stays at 100K tokens or less; above that it jumps to $0.50 and $2.50. Sonnet 5.5, the workhorse, is $2 and $10. Opus 5.5 is $4 and $20, and Fable 5.1, the most capable, is $10 and $50.

Prompt caching is where Anthropic pulls ahead for agents. A cache read on Sonnet 5.5 costs $0.10 per million instead of $2. And for most Claude models, only uncached input tokens count toward your input-tokens-per-minute limit. At the Start tier that limit is 2,000,000 ITPM on Sonnet, Opus and Haiku, with 4,000 requests per minute. An agent that resends the same system prompt and files every turn gets cheaper and hits the ceiling later. Batch takes another 50% off.

On data: by default, Anthropic doesn't train on inputs or outputs from its commercial API. There's no EU region. If you need requests processed only in the US, US-only inference costs 1.1x the standard input and output price.

The catch is the monthly spend cap. Start tier stops at $500 a month, Build at $1,000, Scale at $200,000. Hit the cap and the API returns 429 errors until the first of the next month. Brand-new organizations can also start in an Evaluation tier, below standard limits. Fast mode on Opus 5.5 bills at twice the normal rate.

Hack: split usage into one workspace per project or customer, each with its own key and spend limit. Read our full Anthropic review for the rest.

OpenAI's price list has more rungs than anyone else's. At the bottom, gpt-5-nano is $0.05 input and $0.40 output per million tokens, and gpt-6-luna is $0.10 and $0.50. In the middle, gpt-6.1-terra runs $1 and $5, gpt-6.1-sol $2 and $10. At the top, gpt-6-astra is $10 and $50. Those rates apply to requests up to 272K input tokens.

Two modes cut the bill in half. Batch runs your requests asynchronously; Flex runs them when spare capacity is available. On gpt-6.1-sol, both bring the price to $1 input and $5 output. Going the other way, Fast mode (formerly Priority) doubles it, to $4 and $20. Cached input is cheap: $0.10 instead of $2 on gpt-6.1-sol.

On data: API traffic isn't used to train OpenAI models unless you opt in. Abuse-monitoring logs are kept for up to 30 days, and Zero Data Retention is available with approval. There's a European region (EEA plus Switzerland) at eu.api.openai.com, but only for accounts approved for those abuse-monitoring controls, under an amendment to your contract.

The catch: regional data-residency endpoints carry a 10% uplift on the newest models. And model names change several times a year, so pin the exact model version in your code. If you're weighing a move away, our page on switching from OpenAI covers the alternatives and the migration.

Hack: start classification, extraction and summarization jobs on gpt-6-luna. At $0.10 input it's 20 times cheaper than gpt-6.1-sol. Move up a tier only where your evals show the quality isn't there.

The Gemini API is the only big-name API with a free tier on a current model: Gemini 3.8 Flash works at no cost within free-tier limits. Paid prices start very low. Gemini 2.5 Flash-Lite is $0.10 input and $0.40 output per million tokens, 3.1 Flash-Lite $0.25 and $1.50, 3.5 Flash-Lite $0.30 and $2.50, and 3.8 Flash $0.75 and $3.75. Gemini 4 Argon, the most capable, is $2 and $10 for now, then $4 and $20 after the announced increase ($2 and $10 in batch), and isn't on the free tier.

Free comes with strings. On the free tier, Google uses your data to improve its products, and human reviewers may read, annotate and process your API input and output. Google's terms also say that if your app serves users in the EEA, the UK or Switzerland, you may use only paid services. Once you pay, your data is no longer used to improve the products.

Paid tiers unlock with history. Tier 1 needs a linked billing account and caps spend at $250. Tier 2 needs $100 already paid and 3 days, with a $2,000 cap. Tier 3 needs $1,000 and 30 days. Requests-per-day quotas reset at midnight Pacific time.

The catch: the lineup shifts under you. Gemini 2.5 Pro and 2.5 Flash are deprecated and will be routed to 3.8 Flash and 3.5 Flash-Lite at the end of 2026. Two prices also double: Gemini 4 Argon is set to go to $4 and $20 soon, and Gemini 3.8 Flash to $1.50 and $7.50 in early 2027. Your cost and output can change without a single code change. Our Gemini review covers the rest.

Hack: build and test on the free tier, then link billing before launch. You move to Tier 1 the same day, and your traffic drops out of product-improvement use.

Mistral AI, the French lab, is one of the providers here whose current models ship with open weights, alongside OpenAI's gpt-oss and DeepSeek's V4. Mistral Small 4 and the Ministral 3 family are Apache 2.0, and Mistral Large 4 is open-weight under Mistral's own license. Call them through the API now, self-host later, keep the same model.

Prices are low for a frontier-class lineup. Mistral Large 4 is $0.70 input and $2.10 output per million tokens; Small 4 is $0.15 and $0.60. The small Ministral 3 models charge the same for input and output: $0.10 for 3B, $0.15 for 8B, $0.20 for 14B. Codestral, the coding model, is $0.30 and $0.90. Mistral also hosts third-party models such as GLM 5.3 and DeepSeek V4.1 Flash, and its moderation model is free.

On data, get the processing region written into your contract. Read the data processing addendum closely: Mistral may train on customer data unless the customer has opted out. Flip that switch before you send anything real.

The catch: the free tier's limits aren't published anywhere, only in the console. And Mistral's marketing page still quotes an older Large price ($0.50 / $1.50) that contradicts the docs; budget from the docs.

Hack: for ticket tagging or field extraction, Ministral 3 8B at $0.15 per million for both input and output costs a quarter of Small 4's output price.

DeepSeek is the cheapest capable API in this ranking. deepseek-flash (V4.1 Flash) costs $0.30 input and $1.20 output per million tokens at peak, and cached input drops to $0.006. deepseek-v4-pro, the stronger model, is $1.32 and $3.96. deepseek-flash and deepseek-v4-pro both take a 1M-token context and can write up to 384K tokens in one response.

The twist is off-peak pricing, at half the peak rate. Peak runs 01:00 to 04:00 and 06:00 to 10:00 UTC, Monday to Friday; everything else, evenings and weekends included, is off-peak. deepseek-flash drops to $0.15 and $0.60 off-peak.

The catch is a hard one: DeepSeek's privacy policy says it collects, processes and stores personal data in the People's Republic of China. For customer data, that's a legal question before it's a technical one.

Hack: if you want DeepSeek's price without sending data to China, other hosts serve the same model. Mistral and Together AI list DeepSeek V4.1 Flash at $0.30 / $1.20.

OpenRouter isn't a model, it's a router. One key and one API format put 600+ models behind a single endpoint, from Anthropic, OpenAI, Google, Mistral, DeepSeek and more. Switching models means changing one string.

You pay the provider's price plus a 5.5% platform fee (Standard plan) each time you buy credits. Bring your own provider keys (BYOK) and the first $25,000 of usage a month carries no fee, then 5%. Rate limits pass through from the provider. The free tier offers 25+ free models at 50 requests a day and 20 a minute, rising to 1,000 free requests a day once you've bought $10 in credits.

The catch is everything around the routing. OpenRouter reserves the right to expire unused credits a year after purchase, refunds unused credits only within 24 hours, and never refunds platform fees or crypto payments.

Hack: top up in small amounts. With credits that can expire after a year, paying the 5.5% more often beats parking a large balance. And for the one model you run in production every day, go direct.