Capital & Compute

AI Model Comparison

Tool· Rates as of October 2026

Put two or three models head to head on the same coding task. The price list compares the sticker rate; this compares what a real task actually costs to finish, which is the number that lands on your invoice.

How do I compare the cost of two AI models?

Compare them on cost per task, not on the price list. Multiply each model's input and output rates by the tokens a real job actually consumes, then compare the totals. A model with the lower per-token sticker can still cost more to finish the same work, which is exactly what the sticker comparison hides.

Compare models on one task

Modeled estimate

On this task, Grok 4.5 is the cheapest to finish at $0.945/task, about 7% less than Pareto 26.9 ($1.01).

Pareto 26.9 UnbiasedGrok 4.5 xAI
Cost / task$1.01 $0.945 cheapest
At 3/day$66.82/mo$62.37/mo
Input $/Mtok$2.5$2
Output $/Mtok$7.5$6
Cache read $/Mtok$0.25$0.3
ReleasedSep 2026Jul 2026
Where the money goes
  • Cache reads 33%
  • Fresh input 37%
  • Output 30%
  • Cache reads 43%
  • Fresh input 32%
  • Output 25%

Each model is costed on the same task profile from its published per-token API rates, so the comparison is apples-to-apples. This is a modeled estimate, not a benchmark: real cost varies with your codebase and how tightly you scope each request. Open the full cost-per-task calculator to rank every tracked model at once.

Why compare on cost per task, not the price list

Two models with very different per-token rates can cost almost the same to finish a job, and two with similar rates can be far apart. What you pay is set by how many tokens the task burns: the repeated context an agent re-reads each turn (billed at the cache rate), the fresh input it sees once, and the output it generates. A model with a low sticker price but a high output rate can lose to a pricier-looking model on an output-heavy task. A 2026 Microsoft Research preprint found this reversal in 32% of model pairs. The mechanism is the subject of the price reversal phenomenon.

Popular matchups, costed on a multi-file change

Each figure below is modeled on the same multi-file change profile (1.5M input tokens, 90% served from cache, 40k output) from each provider's published API rates. Set your own task shape in the tool above to see how the gap moves.

Claude Fable 5.1 vs Claude Opus 5.5

On this task, Claude Fable 5.1 runs about $3.84 per task and Claude Opus 5.5 about $1.67. Claude Opus 5.5 is roughly 56% cheaper to finish the same work. Compare them in the tool or adjust the task shape to test an output-heavy or longer-context job.

Gemini 3 Flash vs Claude Haiku 4.5

On this task, Gemini 3 Flash runs about $0.262 per task and Claude Haiku 4.5 about $0.485. Gemini 3 Flash is roughly 46% cheaper to finish the same work. Compare them in the tool or adjust the task shape to test an output-heavy or longer-context job.

How the cost is modeled

For each model, the cost of one task is cache reads (the repeated context, billed at roughly a tenth of fresh input on most models, a twentieth on Claude Opus 5.5, a fortieth on Claude Fable 5.1, or near zero on DeepSeek) plus fresh input plus output, each at the provider's official per-token rate, multiplied by any loops or retries. Every rate is read from the provider's API pricing page and dated; see the AI coding plan pricing comparison for the subscription side and the AI model release tracker for release dates and what is coming next. To rank all 40 models on one task at once rather than a chosen few, use the cost-per-task calculator.

Treat the number as a range, not a point

These figures are modeled from published prices and stated assumptions. They are not a benchmark and they are not your bill. The same task run twice on the same model can vary in cost by nearly an order of magnitude, because how long a model reasons is partly random. Use the comparison to size the order of magnitude and to see which model is structurally cheaper for the work, then plan against the expensive tail.

Frequently asked questions

How do I compare the cost of two AI models?

Compare them on the same task, not on their per-token price lists. The sticker rate (dollars per million tokens) does not tell you what a real coding task costs, because that depends on how many input, cache and output tokens the task burns. Modeled on one multi-file change, Claude Fable 5.1 runs about $3.84 per task and Claude Opus 5.5 about $1.67, so Claude Opus 5.5 is roughly 56% cheaper to finish the same work.

Is a cheaper per-token model always cheaper to use?

No. A model with a lower per-token sticker can cost more to finish a task if it generates more output or burns more reasoning tokens. This price reversal showed up in 32% of model pairs in a 2026 Microsoft Research preprint. Comparing on cost per task, rather than the price list, is the only way to see it.

Which AI model is cheapest for coding tasks?

On a modeled multi-file change across the 40 models tracked here, the cheap-token models (GPT-6 Luna, GLM-5.3-Flash, DeepSeek V4 Flash) come out lowest, while the premium Claude Fable tiers cost the most per task. The order shifts with the task shape: output-heavy work narrows the gap, and cache-heavy work rewards a low cache-read rate, which is how Claude Fable 5.1 lands about 21% under Claude Fable 5 on identical per-token rates. Claude Opus 5.5, released September 22, cut both at once: 20% off the sticker at $4 and $20 per million tokens, and 60% off the cache read at $0.20. That is why the comparison lets you set the task profile.

What is the difference between this and the cost calculator?

The calculator ranks every tracked model on one task at once and is best for finding the single cheapest option. This comparison puts two or three specific models head to head with their full rate cards, release dates and per-task cost breakdown side by side: better for a deliberate "X versus Y" decision.

Sources

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