There isn’t one best LLM for every job. For demanding reasoning and coding, compare OpenAI GPT-6 Astra, Google Gemini 4 Argon, and Anthropic Claude Opus 5.5. For a general-purpose starting point, consider GPT-6.1 Sol, Claude Sonnet 5.5, or Gemini 3.8 Flash. For high-volume, cost-sensitive tasks, shortlist GPT-6 Luna, Gemini 3.5 Flash-Lite, or Claude Haiku 5.5. These are candidates to evaluate based on provider-documented positioning—not winners of independent head-to-head testing.
Prices and availability below are stated as of November 10, 2026. Prices are USD per 1 million tokens unless noted. Promotional rates, feature support, and limits can depend on provider, API, and service tier.
Quick picks by use case
| Need | Models to evaluate first | Why they’re on the shortlist | Main trade-off |
|---|---|---|---|
| Hard reasoning, coding, and complex knowledge work | GPT-6 Astra (gpt-6-astra); Gemini 4 Argon (gemini-4-argon); Claude Opus 5.5 (claude-opus-5-5) |
Their providers position them for demanding reasoning, software engineering, or agent work. | Premium models cost more per token; test whether the added capability improves your task outcomes. |
| General-purpose API applications | GPT-6.1 Sol (gpt-6.1-sol); Claude Sonnet 5.5 (claude-sonnet-5-5); Gemini 3.8 Flash (gemini-3.8-flash) |
Each is a candidate when you need capability without automatically choosing the highest-priced tier. Google recommends Gemini 3.8 Flash for everyday apps and agents. | These models aren’t interchangeable. Test your prompts, tools, and output requirements. |
| High-volume, cost-sensitive text and workflow tasks | GPT-6 Luna (gpt-6-luna); Gemini 3.5 Flash-Lite (gemini-3.5-flash-lite); Claude Haiku 5.5 (claude-haiku-5-5) |
Providers position these models for efficiency, speed, or high-volume work. Anthropic describes Haiku 5.5 for classification, extraction, routing, and similar latency-sensitive tasks. | Confirm quality on difficult cases before routing important work to a lower-cost model. |
| Coding and multi-step agent workflows | Claude Opus 5.5 or Sonnet 5.5; GPT-6 Astra or Sol; Gemini 4 Argon or 3.8 Flash | Their API documentation describes coding, agent, tool-calling, or computer-use capabilities. | Tool support and constraints differ by model and API. Check the exact configuration you intend to deploy. |
| Current information in a text workflow | Grok 4.7 (grok-4.7) |
xAI documents API search tools for using live web or X information in requests. | Fresh information depends on enabling the relevant search tool; the model alone does not make its training knowledge current. |
This is a practical starting shortlist, not a complete directory or neutral leaderboard. Provider documentation describes each company’s own models; it does not establish an overall winner across providers.
Current API models and listed prices
| Provider and model | Listed API price: input / output | Useful distinction |
|---|---|---|
OpenAI GPT-6 Astra (gpt-6-astra) |
$10 / $50 | OpenAI positions it for complex reasoning and coding. |
OpenAI GPT-6.1 Sol (gpt-6.1-sol) |
$2 / $10 | Supports text and image input, function calling, and structured outputs; tool calling requires the Responses API. Its documented limit is 1,050,000 context tokens and 128,000 output tokens. (developers.openai.com) |
OpenAI GPT-6 Luna (gpt-6-luna) |
$0.10 / $0.50 | OpenAI positions it for focused, high-volume tasks. |
Anthropic Claude Opus 5.5 (claude-opus-5-5) |
$4 / $20 | Anthropic positions it for advanced coding, agents, and knowledge work. |
Anthropic Claude Sonnet 5.5 (claude-sonnet-5-5) |
$2 / $10 | Active on Anthropic’s API and named cloud platforms; documented limits are 1 million context tokens and 128,000 output tokens. (platform.claude.com) |
Anthropic Claude Haiku 5.5 (claude-haiku-5-5) |
From $0.10 / $0.50 | Anthropic lists it for high-volume, latency-sensitive tasks. The lower rate applies to prompts up to 100,000 tokens; higher prompt lengths have higher input and output rates. (platform.claude.com) |
Google Gemini 4 Argon (gemini-4-argon) |
$2 / $10 introductory price through Nov. 30; then $4 / $20 | Google’s documented API model has a unified 1-million-token context window. (ai.google.dev) |
Google Gemini 3.8 Flash (gemini-3.8-flash) |
$0.75 / $3.75 introductory price through Dec. 31 | Google recommends it for everyday apps and agents. The standard price applies after the introductory period. |
Google Gemini 3.5 Flash-Lite (gemini-3.5-flash-lite) |
$0.30 / $2.50 | Google positions it for high-volume work such as document parsing and data extraction. |
xAI Grok 4.7 (grok-4.7) |
$2 / $6 | xAI documents search tools as an API option for live information. |
The Gemini 3.8 Flash API documentation lists function calling and structured outputs, a 1,048,576-token input limit, and a 65,536-token output limit. (ai.google.dev) Prices are provider-listed token rates, not a total-cost comparison. Caching, batch processing, long-context surcharges, tool calls, media input, hosting platform, and service tier can change the bill. Google’s API documentation also distinguishes free and paid tiers; check the data-use terms and limits for the exact channel you plan to use.
A simple cost example
Suppose aggregate usage across multiple requests in a billing period totals 1 million input tokens and 250,000 output tokens. At the listed base token rates, the illustrative subtotal—before caching, tools, or other charges—would be:
- GPT-6 Astra: $22.50 ($10 input + $12.50 output).
- GPT-6.1 Sol or Claude Sonnet 5.5: $4.50 ($2 + $2.50).
- Gemini 4 Argon at its introductory rate: $4.50; at its listed later rate: $9.00.
- Grok 4.7: $3.50 ($2 + $1.50).
- Gemini 3.8 Flash at its introductory rate: about $1.69 ($0.75 + about $0.94).
These are aggregate base-rate calculations, not a claim that any one request can contain that many input and output tokens, or a prediction of your complete bill. Check the per-request input and output limits and any applicable long-context or other charges for the exact model and API channel.
How to choose the right model
- Define the task and success criteria. For support answers, that could mean correct resolution and acceptable tone. For coding, it might mean passing tests without unwanted edits. For extraction, it might mean field-level accuracy.
- Shortlist two or three candidates. Include a lower-cost option and, for consequential work, a more capable tier for comparison.
- Run the same representative cases on each. Use realistic inputs, including ambiguous and difficult examples—not only prompts each model is likely to handle easily.
- Score outcomes, not reputations. Track task success, mistakes, response time, and cost per completed task. For tool-using applications, record failed or unnecessary tool calls too.
- Check production fit. Confirm the exact model ID is available in your API channel and supports the inputs, tools, output format, and limits your application needs.
Benchmarks can help narrow a shortlist, but they do not establish which model will work best with your prompts, data, tools, and latency target. If you publish results from your own tests, state the model IDs, date, task set, scoring criteria, and test conditions. Don’t present provider positioning or an informal comparison as a controlled cross-provider evaluation.
Production API checks before you commit
The following API-specific details help screen three general-purpose finalists against common tool, structured-output, and size requirements:
| Model | API access and documented capabilities | Context and output limits |
|---|---|---|
GPT-6.1 Sol (gpt-6.1-sol) |
OpenAI API; Chat Completions and Responses endpoints are supported. Function calling and structured outputs are documented. Tool calling requires the Responses API. | 1,050,000 context tokens; 922,000 maximum input tokens; 128,000 maximum output tokens. (developers.openai.com) |
Claude Sonnet 5.5 (claude-sonnet-5-5) |
Available through the Claude API and named cloud platforms. Anthropic documents agentic tool use for this model; Claude API documentation describes JSON outputs and strict tool-use schema validation. | 1 million context tokens; 128,000 maximum output tokens. (platform.claude.com) |
Gemini 3.8 Flash (gemini-3.8-flash) |
Stable model available through the Gemini API. Function calling and structured outputs are listed capabilities. | 1,048,576 input tokens; 65,536 maximum output tokens. (ai.google.dev) |
These limits are provider-documented model limits, not a guarantee that every API route, account, or request configuration has identical availability. Verify quotas, service limits, supported schema features, and tool behavior on the exact endpoint or cloud platform you will use. For example, GPT-6.1 Sol tool calls require OpenAI’s Responses API; do not assume tool behavior is identical across endpoints. (developers.openai.com)
- Pin the version when consistency matters. Check whether the provider offers a dated snapshot or stable model ID; aliases can change as models are updated.
- Check API-specific features. A feature in a consumer chat app is not automatically available through an API. Verify the modalities, tools, and output controls for the actual model and endpoint.
- Budget the actual workload. Estimate input and output tokens separately, then include caching, tool use, batch discounts, media, and platform charges where applicable.
- Review privacy and contractual terms. Data handling can depend on provider, tier, and deployment route. Don’t infer it from the model name alone.
Bottom line
For a first-round general-purpose API evaluation, compare GPT-6.1 Sol, Claude Sonnet 5.5, and Gemini 3.8 Flash. Add GPT-6 Astra, Gemini 4 Argon, or Claude Opus 5.5 if your hardest tasks justify a higher-cost tier. For routine high-volume work, test GPT-6 Luna, Gemini 3.5 Flash-Lite, or Claude Haiku 5.5 against your quality threshold. If freshness is essential, evaluate Grok 4.7 with the required search tool enabled—or compare another model with a verified retrieval setup.
The best choice is the least expensive model that reliably meets your measured quality, latency, and API requirements—not automatically the highest-priced or highest-profile one.
Sources
GPT-6.1 Sol Model | OpenAI API
Claude Sonnet 5.5 | Claude Platform Docs
Claude Haiku 5.5 | Claude Platform Docs
Structured outputs | Claude Platform Docs
What's new in Gemini 4 Argon | Gemini API