Kimi K3.1 Pro vs GPT-6.1 Sol: Two Paths for Faster Agent LLMs

What are the two models built for?

K3.1 Pro is the first model in Moonshot's K3.1 series. It builds on Kimi K3, with further training aimed at coding, 3D creation, financial research and longer agent tasks. Moonshot describes it as a 3T-class model. You can use it through Kimi's apps, Kimi Code and the API. The company says full weights will arrive by November 4, 2026; that is a separate step from hosted access.

GPT-6.1 Sol occupies a lower price tier than Astra in OpenAI's GPT-6 lineup. Its launch focused on agentic coding, computer use and professional work. It shipped through the API, ChatGPT Work and Codex on eligible paid plans, with Chat access absent at launch. Sol is a separate model choice, rather than an Astra speed setting.

Where does the speed come from?

Kimi K3.1 Pro: choose how the same model is served

Moonshot offers two API IDs: kimi-k3.1-pro and kimi-k3.1-pro-highspeed. Its advertised Highspeed gain is 2 to 3 times faster generation. The October 24 CNY price snapshot lists standard input and output at CNY 13 and CNY 68 per million tokens, versus CNY 26 and CNY 136 for Highspeed. Cached input remains CNY 1.3 for either option.

A team can route an interactive edit to Highspeed and leave a nightly batch on standard. That keeps the model choice consistent, but the application needs to decide when faster output is worth the higher rate. A generation speed claim also does not tell you how much faster an entire task will finish once tool calls and retries are included.

Kimi's thinking mode stays enabled. Set reasoning_effort to low, high or max; the default is max. For a simple request, lowering effort is the available way to reduce reasoning work.

GPT-6.1 Sol: a separate model with its own speed options

OpenAI positions Sol below Astra on price while aiming to retain much of its capability. Choosing Sol makes that tradeoff at the model level. For a team already using Astra, moving routine jobs to Sol is a model-selection decision. Check the quality on your own tasks before moving harder work.

Sol also has serving choices. Current API documentation lists Fast and Ultrafast, so teams can choose Sol for its price and capability, then decide whether a faster tier is worth paying for.

Where does the agent loop run?

Kimi Code gives developers an agent environment they can extend. Its desktop, CLI and VS Code clients support an environment with MCP servers, plugins, hooks and subagents. Its examples include external tools such as Blender, CAD software and game engines. When using an intermediary, check the protocol and tool behavior your task needs; translating a request format is another integration step to validate.

Sol is available inside OpenAI's Codex and ChatGPT Work, as well as through the API. OpenAI's September 29 changelog introduced hosted browser computer use in the Agents API, with the integrating application responsible for website approvals and sign-in. Teams can use the hosted environment while keeping access decisions in their application.

What determines the cost of an agent session?

Repeated context makes cached input worth checking. In the October 24 price snapshot, cached input is 10% of the ordinary input rate for standard K3.1 Pro and 5% for standard Sol. Those percentages describe cache reads. They do not include the separate cost of writing a cache or the output generated during a task.

Kimi Code membership is another purchase decision. The October 24 membership snapshot lists K3.1 Pro from Plus or Moderato, and the 1M context and Highspeed options from Pro or Allegretto. Those are membership descriptions, separate from metered API access. The current Kimi API documentation lists a 1M context window; a higher Kimi Code membership should not be presented as a universal API requirement.

The CNY tariff could not be independently rechecked in this review. Treat it as a dated source snapshot, not a current quote. Provider rates in this table are separate from SiAPI.ai pricing.

Sol's current documentation adds conditions that matter for budgeting: standard rates apply through 272K input tokens; longer prompts cost more. Fast is 2 times standard and Ultrafast is 6 times standard. Cache writes and tools can add charges. A lower headline rate alone cannot establish a lower bill across the two providers.

Which workload is a sensible place to start?

Start by trying Kimi on long coding sessions and Sol on repeated tasks in an existing OpenAI setup. These are trial suggestions; the right choice depends on your results. Both APIs now document roughly a million tokens of context.

• Long refactors across a repository: try K3.1 Pro when its Kimi Code environment fits your workflow. Compare completion quality and waiting time on standard and Highspeed. Sol should remain in the trial if your team already works in Codex.
• Batch jobs with short turns: Sol Standard is a practical baseline. Measure its full task cost against Kimi standard before choosing; the original mixed-currency table does not prove which is cheaper.
• 3D, CAD and game engines: Moonshot explicitly demonstrates these workflows. Test a task with inspectable geometry, dimensions or project files.
• Browser work with approvals: OpenAI's hosted browser is relevant when a managed environment fits. Your application still handles website access and sign-in.
• Existing paid subscriptions: check what your current OpenAI or Kimi membership includes before buying another plan. Product subscriptions and API billing have different terms.

You can also assign different jobs to the two models and evaluate each assignment separately. Keep long sessions on Kimi and repeated work on Sol only if your results support that routing.

What tradeoffs should you check?

K3.1 Pro keeps reasoning enabled, so simple requests still involve a reasoning setting. Highspeed raises ordinary input and output rates while leaving the source snapshot's cache-read price unchanged. Kimi Code membership limits need checking separately from API limits. The promised weight release also does not make local deployment practical on a laptop; a 3T-class model needs substantial infrastructure, and the final release terms still matter.

Sol's tradeoff is the balance of capability, service speed and cost within OpenAI's lineup. Its context window is now documented, and Ultrafast is no longer merely a launch promise. Longer inputs and faster serving change the bill. Managed products also bring their own tool and approval boundaries. None of those details can be inferred from the base input price alone.

Frequently asked questions

Is Kimi K3.1 Pro open source?

Hosted access is available. Moonshot promises full weights by November 4, 2026. An announced weight release does not establish the final license or mean the weights are already downloadable.

Can I turn off thinking on Kimi K3.1 Pro?

No. Its API guide says thinking stays enabled. Use reasoning_effort: "low" to request less reasoning; high and max are also supported, with max the default.

Does GPT-6.1 Sol have a faster serving option?

Yes. Current API documentation lists Fast and Ultrafast. Compare the faster tier with Standard on the same task before paying the premium.

Which model is cheaper per token?

A CNY-versus-USD price table cannot settle that comparison. Use a common currency and the applicable service tier, then include caching, reasoning output and retries. For choosing an agent, cost per successful task is usually more useful than a single token rate.