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Model comparison
Inkling vs Celeris-1 Magnus
Compare Inkling and Celeris-1 Magnus using the same provider-sourced text & reasoning rubric. No mystery score and no invented benchmark ranking.
Facts checked September 4, 2026
Estimate your cost
Set your usage. Your estimate updates as you type.
Example: 6,000 input tokens for 10 pages, plus a 500-token summary. Page lengths vary; adjust the numbers below.
One run sends your input to the model once and receives an answer. Tokens are pieces of text: input is what you send, output is the answer you receive.
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How this estimate works
Estimates exclude taxes, tools, cache storage/writes, free allowances and custom discounts. Image estimates cover output only, not prompt or reference-image charges. Quality modes differ by model. Unlisted settings are not treated as free.
| Model | Access | Estimated total (USD) |
|---|---|---|
| Celeris-1 MagnusCeleris | Celeris | No reviewed rate |
| InklingThinking Machines Lab | Thinking Machines Lab | No reviewed rate |
Quick take
Inkling
Thinking Machines Lab's large open-weights model for customizable reasoning, coding, tools, vision, and audio workflows.
Best for
- Teams that want an adaptable open-weight foundation model
- Agentic coding and tool-use experiments
- Private or specialized deployments with multimodal inputs
Watch out for
A 975B model is a serious serving project even with sparse activation. Compare the exact hosted or self-hosted route, and do not assume the model's 1M maximum context is available on every provider.
Celeris-1 Magnus
Celeris' agent-focused diffusion language model for fast reasoning, tool loops, structured actions, and OpenAI-compatible integration.
Best for
- Low-latency tool-using agents
- Structured extraction and action workflows
- Teams migrating an OpenAI-compatible client
Watch out for
The public price page labels Celeris-1 rather than Magnus, and the service remains early. Confirm Magnus billing, capacity, support, data retention, and a production SLA directly.
Compare the published facts
Inkling vs Celeris-1 Magnus
Values use each provider's own published units and limits. A blank means the provider did not publish a directly comparable value in the sources reviewed.
| Text & reasoning | Inkling | Celeris-1 Magnus |
|---|---|---|
| Context windowMaximum combined prompt and working context documented by the provider. | Up to 1M tokens; Tinker offers 64K and 256K | 131,072 tokens combined |
| Maximum outputProvider-published response limit, where available. | Not separately published | Any positive limit within the combined context |
| Knowledge cutoffLatest reliable knowledge date explicitly published by the model provider. Search and connected tools can retrieve newer information but do not change the model's built-in cutoff. | Not published | Not published |
| Input priceCurrent standard list price per million input tokens unless noted. | Hosting dependent | $0.20 / 1M listed family rate; verify Magnus |
| Output priceCurrent standard list price per million output tokens unless noted. | Hosting dependent | $0.70 / 1M listed family rate; verify Magnus |
| InputsMedia types accepted by the listed model endpoint. | Text, image, audio | Text; image content parts supported by the API |
| Tools & agentsSelected native tools and agent-building capabilities, not an exhaustive list. | Agentic coding, tools, Python-assisted vision, controllable thinking | Tools, JSON schema, reasoning low/medium/xhigh |
How to choose
Compare the job, not the hype.
Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.
Inkling
The open weights can be self-hosted so request data stays in infrastructure you control. Tinker and partner-hosted routes have separate retention and training-use terms that must be checked with the selected provider.
Celeris-1 Magnus
Celeris says API inputs and outputs are processed to provide the service and monitor abuse and reliability. Its public notice does not give one fixed content-retention period or no-training promise; enterprise VPC options are available.
Provider and API links
Frequently asked questions
Inkling vs Celeris-1 Magnus FAQ
What is the main difference between Inkling and Celeris-1 Magnus?
Inkling: Thinking Machines Lab's large open-weights model for customizable reasoning, coding, tools, vision, and audio workflows. Celeris-1 Magnus: Celeris' agent-focused diffusion language model for fast reasoning, tool loops, structured actions, and OpenAI-compatible integration.
Should I choose Inkling or Celeris-1 Magnus?
Consider Inkling when your priority is Teams that want an adaptable open-weight foundation model. Consider Celeris-1 Magnus when your priority is Low-latency tool-using agents. Test both with your own data and provider route before committing.
Is this Inkling vs Celeris-1 Magnus comparison based on Cody benchmarks?
No. This comparison aligns provider-published facts for the Text & reasoning category. It does not claim a universal winner or combine incompatible third-party benchmark scores.