I Tracked LLM Pricing for 8 Weeks. Here's What the Data Shows

I Tracked LLM Pricing for 8 Weeks. Here's What the Data Shows. | Token PricesSign in

The Problem That Started This A few months ago, I was building an AI product and hit a wall: Which LLM should we use? The question sounds simple. But the pricing landscape for AI models shifts constantly and without warning. OpenAI has 69 models listed on their pricing page. Google has 18. Anthropic launched three new Claude versions in the span of weeks. By the time I had compared options and made a decision, I had no confidence the numbers were still current. I checked pricing pages. I checked docs. I found no single place that told me: What did this cost last week vs. today? Which providers actually changed their prices recently? How wide is the spread for comparable models? So I automated it. Starting April 24, 2026, I built a daily scraper that pulls pricing data from every major provider. Here is what 8 weeks of data actually shows.

1,111models tracked 33providers 59days of data 5price changes detected

Finding 1: The Big Providers Did Not Move The headline finding is not dramatic: Anthropic, OpenAI, Google, Mistral, and xAI all held their prices flat for the entire 59-day period. Not a single price change detected across those five providers. That is useful information on its own. If you are budgeting around these providers, your cost model from April is still accurate today. Here is the current pricing snapshot for the most-used models, accurate as of June 22: ModelInput / 1M tokensOutput / 1M tokensNoteopenai / gpt-4-turbo$10.00$30.00Stable since Apr 24openai / gpt-4o (chatgpt-4o-latest)$5.00$15.00Stable since May 12anthropic / Claude Sonnet 4.5$3.00$15.00Stable since Apr 24anthropic / Claude Opus 4.5$5.00$25.00Stable since Apr 24anthropic / Claude Haiku 4.5$1.00$5.00Stable since Apr 24google / Gemini 2.5 Pro$1.25$10.00Stable since Apr 26google / Gemini 2.5 Flash$0.30$2.50Stable since Apr 26google / Gemini 2.0 Flash$0.10$0.40Stable since Apr 26mistral / Codestral$1.00$3.00Stable since Apr 24xai / Grok 4.3$1.25$2.50Stable since May 16 For teams budgeting: The major closed-model providers are behaving predictably right now. Your April cost model is still valid. That said, 8 weeks is a short window. Pricing for these providers has historically shifted without notice.

Finding 2: The Pricing Spread is Enormous The bigger story is not volatility. It is the 600x price range that now exists across the tracked catalog, from sub-cent inference to frontier flagship models. ModelInput / 1M tokensOutput / 1M tokensNotegroq / llama-3.1-8b-instant$0.05$0.08Cheapest trackeddeepseek / deepseek-v4-flash$0.14$0.28google / Gemini 2.0 Flash$0.10$0.40deepseek / deepseek-v4-pro$0.44$0.87xai / Grok 4.3$1.25$2.50anthropic / Claude Sonnet 4.5$3.00$15.00openai / gpt-4-turbo$10.00$30.00openai / gpt-5.4-pro$30.00$180.00Highest-cost frontier tracked Groq's Llama 3.1 8B costs $0.05 per million input tokens. GPT-4 Turbo costs $10.00 (200x). GPT-5.4 Pro costs $30.00 (600x). All three are in our dataset today. DeepSeek V4 Pro at $0.44 per million input tokens consistently ranks near the top on reasoning benchmarks at a fraction of the flagship price. The question teams should be asking is not just “which model is best?” but “which model is best for this specific task given the cost?” For many production workloads, the answer is not the model you started with. Real cost difference: A team running 100M input tokens per month on GPT-5.4 Pro spends $3,000. The same usage on GPT-4 Turbo costs $1,000. On DeepSeek V4 Pro it is $44. On Groq's Llama 3.1 8B it is $5. The right answer depends entirely on what the task requires, but most teams never run this comparison after their initial model choice.

Finding 3: All 5 Price Changes Came from One Provider Over 59 days, our scraper detected 5 pricing changes across all 1,111 models. Every single one was on Together AI , a hosting aggregator that runs third-party open-source models. DateModelBeforeAfterChangeMay 27qwen37-max$2.50 / $7.50$1.25 / $3.75-50%Jun 2Qwen3.5-9B$0.10 / $0.15$0.17 / $0.25+70%Jun 2Llama-3.3-70B-Turbo$0.88 / $0.88$1.04 / $1.04+18%Jun 2Meta-Llama-3-8B-Lite$0.10 / $0.10$0.14 / $0.14+40%Jun 17DeepSeek-V4-Pro$2.10 / $4.40$1.74 / $3.48-17% / -21% The biggest move: Qwen37-max dropped 50% overnight on May 27, with no public announcement that reached mainstream channels. Teams running that model through Together AI saw their costs cut in half. Teams not monitoring pricing had no idea. Three models saw price increases on June 2: Qwen3.5-9B (+70%), Llama-3.3-70B-Turbo (+18%), and Meta-Llama-3-8B-Lite (+40%). Not all pricing movement favors the buyer. Why this matters: None of these changes came with direct user notifications. No email, no in-dashboard alert, no API changelog. The only way to know was to check the pricing page, which almost nobody does after the initial setup.

Finding 4: No Provider Notifies You Directly Across all 5 detected changes, the announcement path was the same: nothing...

I Tracked LLM Pricing for 8 Weeks. Here's What the Data Shows

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