Specifications
Context Window
—
Input Price/1M
$0.20
Output Price/1M
$0.70
Parameters
—
Speed
1575 tok/s
Latency (TTFT)
630ms
Benchmarks
Celeris-1 results on the main AI model evaluation benchmarks. Higher scores indicate better performance.
Coding
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| SciCode | 21.0 | 100.0 | — |
| AA Coding Index | 14.4 | 100.0 | Artificial Analysis official API |
Knowledge
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU-Pro | 78.0 | 100.0 | — |
Long Context
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA-LCR | 27.0 | 100.0 | — |
overall
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| AA Intelligence Index | 12.5 | 100.0 | Artificial Analysis official API |
Reasoning
| Benchmark | Score | Maximum | Methodology |
|---|---|---|---|
| MMLU Pro | 78.0 | 100.0 | Artificial Analysis official API |
| GPQA Diamond | 63.0 | 100.0 | Artificial Analysis official API |
| HLE | 7.0 | 100.0 | — |
Information
- Release date
- July 24, 2026
- Tool Calling
- ❌ Not supported
- Vision
- ❌ Not supported
- Audio
- ❌ Not supported
Full Analysis: Celeris-1
What is Celeris-1?
Celeris-1 is an AI model developed by Unknown, classified as a large language model (LLM). It focuses on text processing and natural language generation. As a proprietary model, it is available via Unknown's cloud API.
Pricing & Costs in 2026
Celeris-1 is usage-based, priced at $0.2/1M input tokens and $0.7/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Benchmarks & Performance
Celeris-1 was evaluated on 8 different benchmarks, covering categories like Coding, Knowledge, Long Context, overall, Reasoning. Results show moderate performance across available evaluations.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Recommended Use Cases
Celeris-1 is suitable for a wide range of AI applications: high-volume chatbots and automated support, text generation, summarization, translation, and general assistance.
Comparison with Alternatives
In the 2026 AI model ecosystem, Celeris-1 competes directly with similarly capable models. Unknown competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Frequently Asked Questions
What is Celeris-1?
Celeris-1 is an AI model developed by Unknown. It is a language model (LLM).
How much does Celeris-1 cost?
Celeris-1 costs $0.2/1M input tokens and $0.7/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
How does Celeris-1 compare with other models?
In available benchmarks, Celeris-1 scored: SciCode: 21/100, AA Coding Index: 14.4/100, MMLU-Pro: 78/100. See the full table above for a detailed comparison.
Is Celeris-1 open source?
No, Celeris-1 is a proprietary model from Unknown. It is available via cloud API. For open source alternatives, check our open source model ranking.
What is Celeris-1 best for?
Celeris-1 excels at general-purpose language tasks.
Last updated: August 10, 2026 • View methodology →