Fastest LLMs under $1/M tokens in 2026: speed and cost ranked
Five LLMs under $1/M input tokens ranked by throughput and quality in 2026. Gemini 2.5 Flash leads on tokens per second; DeepSeek V4 wins on output cost.
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Five LLMs under $1/M input tokens ranked by throughput and quality in 2026. Gemini 2.5 Flash leads on tokens per second; DeepSeek V4 wins on output cost.
Prompt caching cuts LLM API costs up to 90%, but Anthropic, OpenAI, and Gemini implement it differently. Here's how each vendor's billing actually works.
GPT-5 costs $2.13/1k for chat, $4.50 for extraction, $11.25 for summarization. Here's the exact per-token math and where batch saves you 50%.
Semantic caching reduces LLM API spend by 20-70% in production. Here's how embedding-based, prompt-hash, and hybrid caching each break in practice.
Four LLMs, six French translation tasks tested by a judge: idioms, false cognates, literary register. Claude leads overall. Gemini 2.5 Flash is the value pick.
Mixture of Experts models run only a fraction of their parameters per token. Here's why DeepSeek and Mixtral are cheap, and when MoE gets expensive.
Prompt caching and the batch API cut a real Claude API bill from $797 to $127/month in 2026. Full worked example with exact token counts and 2026 pricing.
Eight free LLMs worth actually using in 2026 — ranked by quality ceiling, real rate limits, and the exact point each stops being enough.
Four LLMs, six SQL tasks, one PostgreSQL schema. GPT-4o-mini led with 9 wins over Claude Sonnet 4.5, GPT-4o, and Gemini 2.5 Flash. Here's the full breakdown.
We ran 5 developer tasks through DeepSeek V4 Pro, GPT-5.5, Opus 4.7, and Llama 4. V4 Pro beats GPT-5.5 while costing 4.5x less, but latency averages 28 seconds.
Prompt caching cuts LLM costs 90% on Anthropic and 50% on OpenAI, but only when your workload fits. Here's the exact break-even math per provider.
The exact token-to-word and token-to-character conversion rates for English, code, and non-English LLM input, plus a practical counting recipe.
OpenAI's GPT-5.5 brings a 1M-token context and native computer use to the frontier, at double GPT-5.4's price. Here's what actually changed.
Opus 4.7 scores higher on coding benchmarks and adds 3.75MP vision, but its new tokenizer inflates real cost by up to 35%. Here's what changed.
Your OpenAI bill isn't just input + output tokens. Thinking tokens, JSON retries, and prompt bloat quietly triple costs. Here's how to spot each one in your own app.