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Capital & Compute
Tool· Rates as of June 2026

AI Model Comparison

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 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 Sonnet 4.6 runs about $1.46 per task and DeepSeek V4 about $0.105, so DeepSeek V4 is roughly 93% cheaper to finish the same work.

Compare models on one task

Modeled estimate

On this task, DeepSeek V4 is the cheapest to finish at $0.105/task, about 93% less than Claude Sonnet 4.6 ($1.46).

Claude Sonnet 4.6 AnthropicDeepSeek V4 DeepSeek
Cost / task$1.46 $0.105 cheapest
At 3/day$96.03/mo$6.92/mo
Input $/Mtok$3$0.435
Output $/Mtok$15$0.87
Cache read $/Mtok$0.3$0.0036
Releasednot statednot stated
Where the money goes
  • Cache reads 28%
  • Fresh input 31%
  • Output 41%
  • Cache reads 5%
  • Fresh input 62%
  • Output 33%

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 ofthe 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 Sonnet 4.6 vs DeepSeek V4

On this task, Claude Sonnet 4.6 runs about $1.46 per task and DeepSeek V4 about $0.105. DeepSeek V4 is roughly 93% 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.

Claude Opus 4.8 vs GPT-5.5

On this task, Claude Opus 4.8 runs about $2.42 per task and GPT-5.5 about $2.63. Claude Opus 4.8 is roughly 8% 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, 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 theAI coding plan pricing comparison for the subscription side and theAI model release tracker for release dates and what is coming next. To rank all twelve models on one task at once rather than a chosen few, use thecost-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 Sonnet 4.6 runs about $1.46 per task and DeepSeek V4 about $0.105, so DeepSeek V4 is roughly 93% 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 twelve released models tracked here, the cheap-token models (DeepSeek V4, Google Gemini 3 Flash) come out lowest, while the premium tiers (Claude Fable 5, Claude Opus 4.8) cost the most per task. The order shifts with the task shape: output-heavy work narrows the gap, which 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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