Which Frontier LLMs Are Live on CometAPI?
You can access leading GPT, Claude, Gemini, DeepSeek, and Grok models through one CometAPI account. Use the OpenAI-compatible base URL https://api.cometapi.com/v1 for the portable chat route, then change the model value. As of September 3, 2026, the five routes checked here are gpt-5.6-sol, claude-fable-5-1, gemini-3.7-flash, deepseek-v4-pro, and grok-4.6.
This is most useful for developers who want to compare models, move workloads between providers, or add a fallback without maintaining five credentials and five client libraries. The shared chat endpoint covers the portable coreâmessages in, text outâbut provider-specific controls still need testing before a production switch.
Availability note: CometAPI lists all five routes as live on September 3, 2026. Claude Fable 5.1 was released on September 1, while GPT-5.6 remains described as a limited preview. Verify account access, quotas, exact IDs, and current pricing before production use.
Frontier LLM Comparison: Price, Context, and Best Use Case
| Model | Best starting use case | Inputs and limits | CometAPI price / 1M |
|---|---|---|---|
| gpt-5.6-sol | Hard reasoning, coding, security | Text, image â text; verify live limits | $4 input / $24 output |
| claude-fable-5-1 | Long-running agents and research | Text, image â text; 1M / 128K output | $8 input / $40 output |
| gemini-3.7-flash | Fast multimodal agents and coding | Text, image, video, audio, PDF â text; 1.05M / 65.5K | $0.60 input / $3 output |
| deepseek-v4-pro | Cost-efficient text reasoning | Text â text; 1M / 384K output | $0.528 input / $1.584 output |
| grok-4.6 | Agentic coding and xAI search tools | Text, image â text; 500K context | $1.60 input / $4.80 output |
This comparison uses the exact IDs and dated prices on CometAPI model pages. Pin the ID used in evaluation, then recheck the live catalog, pricing page, and changelog before deployment.
How to Connect Once and Switch Models
Start with a CometAPI key. For the common OpenAI-compatible route, keep https://api.cometapi.com/v1 as the base URL and change only the model ID for a portable text request. Add provider-specific reasoning, grounding, or tool controls only after checking that model page.
Change only MODEL to test another route. If you need native featuresâsuch as Anthropic Messages, Gemini content generation, a provider-specific reasoning control, or a Responses API fieldâuse that model's documented endpoint instead of assuming the option is portable.
How Much Do These Frontier Models Cost?
As of September 3, 2026, the following CometAPI rates are listed in USD per one million tokens. Prices can change; cached input, tool charges, long-context tiers, retries, and taxes are excluded.
| Route | Input / 1M | Output / 1M | 1M input + 100K output |
|---|---|---|---|
| gpt-5.6-sol | $4.00 | $24.00 | $6.40 |
| claude-fable-5-1 | $8.00 | $40.00 | $12.00 |
| gemini-3.7-flash | $0.60 | $3.00 | $0.90 |
| deepseek-v4-pro | $0.528 | $1.584 | $0.6864 |
| grok-4.6 | $1.60 | $4.80 | $2.08 |
Why the Cheapest Token Isn't Always the Cheapest Outcome
The sample cost is arithmetic, not a prediction of which model will be cheapest in production. A lower token rate can lose its advantage if a route needs more output tokens, retries, larger prompts, or more human review. Measure cost per accepted result.
Sources: GPT-5.6 Sol, Claude Fable 5.1, Gemini 3.7 Flash, DeepSeek V4 Pro, and Grok 4.6.
Which Frontier Model Should You Start With?
GPT-5.6 Sol: Best for High-End GPT Reasoning
GPT-5.6 Sol is the highest-capability GPT-5.6 tier for hard coding, security analysis, research, and long-running agents. Its CometAPI page lists $4 input and $24 output per million tokens as of September 3, 2026 and still describes the family as a limited preview. Use it when the quality gain justifies the premium, then confirm access and quotas before production.
Claude Fable 5.1: Best for Long-Running Agents
Claude Fable 5.1 is built for long-horizon coding, research, and professional knowledge work. The live page lists a 1M-token context, 128K maximum output, text and image input, and $8 input / $40 output per million tokens. Its published gains focus on agentic benchmarks, but test latency, safeguards, and tool behavior on your own workload.
Gemini 3.7 Flash: Best for Efficient Multimodal Work
Gemini 3.7 Flash combines a 1,048,576-token context with text, image, video, audio, and PDF input. At $0.60 input / $3 output per million tokens on CometAPI, it is a practical starting point for high-throughput coding, web development, and multimodal agents. Google-native grounding and computer-use features still need endpoint-specific validation.
DeepSeek V4 Pro: Best for Low-Cost Text Reasoning
DeepSeek V4 Pro is the lowest-priced text route in this five-model snapshot at $0.528 input / $1.584 output per million tokens. Its 1M-token context, 384K maximum output, reasoning, and tool calls suit coding and long-document work. Because it is text-only, route image inputs elsewhere.
Grok 4.6: Best for xAI Tools and Agentic Coding
Grok 4.6 supports text and image input, a 500K context, configurable reasoning, and both Responses and Chat Completions routes. CometAPI lists $1.60 input / $4.80 output per million tokens. It is a strong candidate for agentic coding and xAI search workflows, but live information requires the relevant Web or X Search tool.
How to Benchmark These Five Models Fairly
Published model benchmarks use different harnesses, tool budgets, context limits, and model snapshots. Combining unrelated scores into one leaderboard would create false precision. A better first test is to send the same production-shaped tasks through the shared endpoint and score outputs with your own acceptance rules.
Use the Same Task and Pass Criteria
| Test | Prompt shape | Pass condition |
|---|---|---|
| Structured extraction | Messy support ticket â fixed JSON schema | Valid JSON and every required field present |
| Code repair | Small repository issue + failing tests | Hidden tests pass; no unrelated changes |
| Grounded answer | Long document packet + citation request | Claims trace to supplied passages |
| Tool use | One function schema + ambiguous request | Correct tool and valid arguments |
| Multilingual support | Same task in English and Chinese | Meaning and required format remain stable |
Measure Cost per Accepted Result
Run at least 20 examples per task. Record task pass rate, p50 and p95 latency, input and output tokens, retry rate, and cost per accepted result. Keep the system prompt, tool schema, documents, and maximum output constant. If a provider-specific option is necessary, report it as a separate test rather than quietly giving one model a different harness.
Catalog-level smoke test: on September 3, 2026, each of the five selected model pages exposed a callable CometAPI route, and each listed either operational, live, or available status. This guide validates the request structure and current catalog evidence; it does not invent live output results without an authenticated account run.
At a Glance: A Quick Decision Table
Choose a starting route by workload, then validate it with the same production-shaped tasks. The table below is a decision shortcut, not a universal quality ranking.
| If your priority is... | Start with | Then validate |
|---|---|---|
| Long-running agents or deep research | claude-fable-5-1 | Latency, safeguards, and tool behavior |
| Top GPT-tier reasoning or hard coding | gpt-5.6-sol | Preview access, quotas, and total cost |
| High-volume multimodal work | gemini-3.7-flash | Native feature parity in the shared route |
| Lowest listed text-token rates | deepseek-v4-pro | Quality, retries, and text-only fit |
| xAI search tools or agentic coding | grok-4.6 | Tool configuration and long-context pricing |
For a production watch process, query the models endpoint, review the public catalog, and subscribe to the changelog. Treat availability, price, and model behavior as versioned dependencies.
Production Checklist Before You Switch
What to Validate Before Routing Traffic
- Use a portable baseline. Start with messages,
max_tokens, and a simple system instruction. Add vendor-specific parameters only after the baseline passes. - Pin, log, and compare. Store the requested model ID, returned model, latency, token usage, and retry count for every evaluation.
- Do not retry every error. Authentication and invalid-model errors need configuration fixes; rate limits and transient 5xx errors may merit bounded retry or fallback.
- Set an output budget. Output tokens carry the higher rate in every price row above.
- Keep a fallback chain task-aware. A text-only route cannot replace a vision request. See CometAPI's model fallback guide for implementation patterns.
FAQ
Can I access GPT, Claude, Gemini, DeepSeek, and Grok with one API key?
Yes. CometAPI exposes models from all five providers under one account. For the portable chat route, use https://api.cometapi.com/v1 and select the model ID per request.
Do I need to install five SDKs?
No for the shared OpenAI-compatible subset. One OpenAI SDK client can call the five model IDs shown here. Install a native provider SDK only when you need provider-specific request or response features.
Can I switch models by changing one line?
Usually, changing the model field is enough for a basic text request. It does not guarantee identical behavior, token limits, tool semantics, safety policies, or support for every parameter.
Which route is cheapest in this snapshot?
For the dated token rates in this article, deepseek-v4-pro has the lowest listed input and output price, followed by gemini-3.7-flash. The lowest cost per successful task can differ once retries, output length, tools, and review are included.
Which model is best overall?
There is no defensible universal winner. Use your production task set: GPT-5.6 Sol for difficult GPT-tier work, Claude Fable 5.1 for long-running agents and research, Gemini 3.7 Flash for efficient multimodal workflows, DeepSeek V4 Pro for low-cost text reasoning, and Grok 4.6 for xAI-oriented agent and search workflows.
Can CometAPI automatically fall back if one provider fails?
You can implement a fallback chain around the shared endpoint and keep the same credential. Trigger fallback only for errors and task types you have defined; do not send authentication failures or incompatible multimodal requests blindly to the next model.
Should I use a family alias or an explicit model ID?
Use an explicit ID for evaluation and production. Family aliases are convenient for exploration, but their target, behavior, or price can change.
Build for model change, not model permanence
The practical answer is not to predict one permanent frontier winner. Build a thin model-selection layer, keep the CometAPI base URL stable, pin the five IDs you have tested, and re-run the same acceptance set when availability or pricing changes. That turns a fast-moving model market into a manageable engineering dependency.
Start with the CometAPI Quick Start, verify IDs in the live model catalog, and use the Text and Chat API reference when you move beyond the minimal examples.