Kimi K3
- Input / 1M tokens
- $0.19
- Output / 1M tokens
- $16.00
- Providers
- 18
- Uptime, 24 h
- 100%
API models · Side by side
Kimi K3 vs GPT-6.1 Sol
Kimi K3 and GPT-6.1 Sol both give an application room for long documents and conversations. Kimi adds video input and access to model weights. Sol offers a hosted alternative with a different tool integration and pricing structure. The amount you send and the length of the answer matter more than the headline input rate.
GPT-6.1 Sol
- Input / 1M tokens
- $2.00
- Output / 1M tokens
- $10.00
- Providers
- 3
- Uptime, 24 h
- 100%
The short answer
Consider Kimi for video-based work or a project that needs a self-hosting option. Consider Sol for an application built around its Responses API tools. For text tasks, use the calculator with your input and reply lengths: Kimi’s lower input rate does not mean every request costs less.
Estimate your monthly bill
Enter your own usage. We apply each model's current rates, including long-prompt pricing, for a 30-day month.
Try:
Kimi K3$251.52per month
GPT-6.1 Sol$270.00per month
A token is roughly three-quarters of an English word. Cached input, reasoning tokens, tools and media are not included.
Compare the details
Compare context, supported inputs and usage costs. Highlighted rows show a difference.
| Feature | Kimi K3 | GPT-6.1 Sol |
|---|---|---|
| Input formats | image, text, video | file, image, text |
| Output formats | text | text |
| Context / position limit | 1,048,576 | 1,050,000 |
| Endpoint output limit (tokens) | 943,718 | 128,000 |
| Developer features | frequency penalty, Reasoning output, logit bias, logprobs, Output limit, min p, presence penalty, Reasoning controls, Thinking effort, repetition penalty, Response format, Seed, Stop sequences, Structured output, Temperature, Tool selection, Tool calling, top k, top logprobs, Sampling controls | Reasoning output, Completion limit, Output limit, Reasoning controls, Thinking effort, Response format, Seed, Structured output, Tool selection, Tool calling, Response length |
| Cached input / 1M tokens | $0.18 | $0.10 |
| Cache write / 1M tokens | Unknown | $2.50 |
| USD input / 1M tokens | $0.19 | $2.00 |
| USD output / 1M tokens | $16.00 | $10.00 |
| Available API providers | 18 | 3 |
| Best provider uptime, last 24 h | 100% | 100% |
| Price range across providers (per 1M tokens) | Input $0.18–$4.50, output $9.50–$22.50 across 18 providers | Set by OpenAI |
| Model identifier | moonshotai/kimi-k3 | openai/gpt-6.1-sol |
API pricing
Prices are in USD per million tokens. Input is what you send; output is what the model generates. Chat subscriptions and API usage are billed separately.
GPT-6.1 Sol: long-prompt rates
- Long-prompt threshold: 272,000 prompt tokens. Input: $4.00 / 1M. Output: $15.00 / 1M.
Tools, images and additional reasoning can add charges. The examples below cover input and output tokens only.
Compare local modelsWhat those prices mean in practice
Each example uses the same token budget for both models. These are calculations, not measured workloads. Cache discounts, media, tools and extra reasoning are excluded.
| Workload | Kimi K3 | GPT-6.1 Sol |
|---|---|---|
| 1,000 short requestsPer request: 2,000 input + 500 output tokens | $8.38 | $9.00 |
| 100 document summariesPer request: 20,000 input + 1,000 output tokens | $1.98 | $5.00 |
| 10 long-document requestsPer request: 300,000 input + 2,000 output tokens | $0.90 | $12.30 |
Estimate = requests × (input tokens × input price + output tokens × output price) ÷ 1,000,000. Long-prompt rates are applied where the pricing data provides them. Real requests can use different amounts of output.
Beyond the price tag
Reading a long brief differs from writing a long answer
A document summary reads much more than it writes. A code generator or report writer can reverse that balance. Kimi has the lower input rate in this comparison, while Sol has the lower base output rate. For a useful budget, enter a typical document and the answer you actually need. A single average token total hides which part of the request you are paying for.
Video is a concrete difference
Kimi accepts video as well as images and text through the compared endpoint. Sol accepts text, images and files, without direct audio or video input. If a task depends on a sequence of on-screen actions, Kimi gives you a relevant option. Sending extracted frames or a transcript to Sol is another approach, but it adds preprocessing and may leave out evidence from the original recording.
Sol changes rates for very long prompts
Sol’s long-prompt tier begins at the 272,000-token threshold used by the calculator. Kimi has no corresponding tier in the rates used here. For a 300,000-token input and 2,000-token reply, Sol’s token cost is $1.23; the calculator shows Kimi’s cost alongside it. These are equal-token calculations, excluding tools, caching and extra reasoning. They do not predict how long either model’s answer will be.
Tool calling depends on your API route
Sol supports tool calling through the Responses API; Chat Completions does not provide that capability for this model. If an existing agent uses Chat Completions, changing only the model identifier will not create a working tool integration. Kimi also exposes tool controls through the compared endpoint. Check the client’s request format, tool arguments and handling of failed calls before switching an application.
Open weights are useful when you need operational control
Kimi’s released weights create a self-hosting option that is separate from renting its API. You would take responsibility for compatible serving software, GPU infrastructure, access controls and updates. That can matter for a deployment with specific operational requirements, but it is not an automatic saving. Compare the cost of keeping a server available with the request volume you expect to send.
Do not confuse reading room with reply length
Both have roughly a million tokens of context. Sol’s output limit is 128,000 tokens; Kimi’s hosting endpoint sets its own ceiling, shown in the table. Context and output limits serve different purposes. For a large deliverable, divide the work into reviewable sections rather than assuming the longest possible answer will be the most useful.
Common questions
Can Kimi run on an ordinary VPS?
Released weights do not establish that a model fits a particular server. Use the hardware calculator for the exact checkpoint, precision, context and runtime; assess GPU and software compatibility separately.
Which should I use for a coding assistant?
Check whether your editor supports the exact model and API route. Compare completed changes, tool errors and retries on representative work before changing the default. This page does not claim independent coding benchmark results.