Kimi K3 vs Claude Sonnet 5.5: What a Coding Task Costs [2026]

This post covers cost per coding task only. For the full model lineup by task, see the task-by-task model guide. For K3 itself (architecture, open weights, launch benchmarks), see the Kimi K3 review.

On input, cached input, and output rates, K3 is exactly 1.5 times the Sonnet 5.5 price ($3 against $2, $0.30 against $0.20, $15 against $10). Cache writes are different: K3 is 1.2 times Sonnet 5.5 on the 5-minute tier ($3.00 against $2.50) and 1.5 times on the 1-hour tier ($6.00 against $4.00). For output, Kimi K2 at $2.50 was about 6x cheaper than Sonnet 4.5 at $15, and that gap is gone for these two models.

If you track prices across providers, the AI API price index shows where both sit among the other current models.

The table below uses an assumed task, not a measurement: an agentic coding run that reads 200,000 input tokens and writes 20,000 output tokens. Swap in your own numbers. The "with caching" rows assume 90% of the input is served from cache, which is also an assumption. Real hit rates vary by workflow. The cached rows count cache reads only and leave out cache-write cost, so they assume a warm cache and understate both bills.

At equal token counts the ratio is 1.5x across input, cached input, and output rates. Once cache writes count, the gap on that part of the bill is 1.2x to 1.5x, so the overall ratio is no longer a flat 1.5x. So the useful question is not "which is cheaper per token" but "how many tokens does each one burn to finish the same task."

K3 would need to finish a task using less than two thirds of the tokens Sonnet 5.5 uses to come out even on the rates above. Third-party data now lists both models:

• Artificial Analysis, a third-party benchmarking site, lists K3 (Max) at 160 million tokens and $2.00 per Intelligence Index task. It lists Sonnet 5.5 (Max) at 420 million tokens and $7.67 per task. They come from Artificial Analysis's own task mix, not from your coding workload, so read them as third-party data rather than a verdict.
• The data is mixed and not directly comparable. The two Artificial Analysis pages show different model-set sizes (118 against 224) and different index scores (44 against 56), so the per-task figures were not measured against the same set of models or on the same scale.
• Anthropic says Sonnet 5.5 "costs up to 30% less for most work" than Sonnet 5, at the same per-token price. That is a claim about its predecessor, not about K3.

Speed also affects cost indirectly. In launch-period Artificial Analysis testing quoted in our K3 review, K3 measured 35 output tokens per second, the slowest of the major flagships then. Anthropic says Sonnet 5.5 generates output 30%+ faster than Sonnet 5, but it has not published a tokens-per-second figure we can compare directly. For interactive coding, waiting on output is a real cost even though it never shows up on the invoice.

These two rows are not a head-to-head. Terminal-Bench 2.1 and 4.0 are different test sets, and the results also depend on the harness each lab used. Anthropic's own announcement compares Sonnet 5.5 with Sonnet 5, which scored 10.3% on version 4.0, so the jump it shows is the improvement over its predecessor. Neither lab has published a score for the other's model on a shared version that we could verify.

We also found no SWE-bench score for Sonnet 5.5 on Anthropic's announcement page, and no matching SWE-bench figure for K3. So this post leaves SWE-bench out rather than guess. The old post's SWE-bench numbers (77.2% and 71.3%) belonged to Sonnet 4.5 and Kimi K2 Thinking and should not be carried over to the current models.

Sonnet 5.5 is the default if

• You pay by the token and want the lower list price. Its input, cached input, and output rates are one third lower than K3's, which costs 1.5 times as much on those rates.
• You want faster output in interactive coding, since Anthropic reports a 30%+ speedup over Sonnet 5 and K3 was the slowest flagship in launch testing.
• You want predictable spend. Anthropic publishes cache read and write prices alongside the base rates.

Kimi K3 is worth testing if

• You need open weights, whether to host the model yourself, fine-tune it, or inspect it. Moonshot released them on July 27 under the Kimi K3 License. Self-hosting a 2.8T-parameter model takes serious infrastructure, so most teams will still use the API.
• You run long autonomous coding jobs where latency per step matters less than finishing the work. The K3 review covers the launch benchmarks and where K3 lost to other models.
• Your own task measurements show it finishing with enough fewer tokens to offset the 1.5x list rate.

You can plug your own token counts into the AI cost calculator, or use the model picker if you want a shortlist across providers.

• Anthropic: Introducing Claude Sonnet 5.5 (pricing, Terminal-Bench 4.0, speed and cost claims)
• Anthropic: models overview (claude-sonnet-5-5, 1M context, 128K max output)
• Anthropic: pricing (cache read and write rates)
• Moonshot AI: API pricing, USD rate card (cache-hit, cache-miss, output, cache write)
• Moonshot AI: Kimi K3 announcement ($0.30/MTok cache-hit input, $3.00/MTok cache-miss input, $15.00/MTok output; Terminal-Bench 2.1 score)
• Moonshot AI: official Kimi K3 model card
• Artificial Analysis (third party) model pages for K3 (Max) and Sonnet 5.5 (Max): 160M output tokens and $2.00 per Intelligence Index task for K3, 420M output tokens and $7.67 for Sonnet 5.5. The two pages use different model sets (118 and 224) and index scores (44 and 56).
• Artificial Analysis launch-period speed figure for K3 (35 output tokens per second) is quoted from our Kimi K3 review, which captured it on July 23, 2026.

Is Kimi K3 cheaper than Claude Sonnet 5.5?

Not per token. Claude Sonnet 5.5 lists at $2 input and $10 output per million tokens. Moonshot's global platform lists Kimi K3 at $3 input, $15 output, and $0.30 cached input in USD (the same rates in CNY are 20, 100, and 2 yuan). On input, cached input, and output rates, K3 costs 1.5 times as much. Cost per task also depends on how many tokens each model uses to finish the job. Artificial Analysis, a third party, lists K3 (Max) at 160M output tokens and $2.00 per Intelligence Index task and Sonnet 5.5 (Max) at 420M output tokens and $7.67 per task, but its two pages use different model sets and index scores, so treat those figures as third-party data that is not directly comparable.

Which scores higher on coding benchmarks, Kimi K3 or Claude Sonnet 5.5?

The published numbers cannot be ranked against each other. Moonshot reports 88.3 for Kimi K3 on Terminal-Bench 2.1, and Anthropic reports 70.6% for Claude Sonnet 5.5 on Terminal-Bench 4.0. These are different benchmark versions, so the two scores do not measure the same thing.

Do Kimi K3 and Claude Sonnet 5.5 have the same context window?

They are in the same range. Kimi K3 lists a 1,048,576-token context window on its model card, and Claude Sonnet 5.5 has a 1M-token context window with up to 128K output tokens according to Anthropic's models overview.

Can I self-host Kimi K3 to save money?

Moonshot released the K3 weights on July 27, 2026, but the model has 2.8 trillion total parameters (104 billion active), so it needs data-center hardware. For most teams the API is the realistic route, and Sonnet 5.5 is not available as open weights.

Written by

Paras Tiwari

Founder, Spectrum AI Labs

Founder of Spectrum AI Labs — testing AI tools and models, and writing up what actually ships.

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