Model comparison
Compare Falcon-H1R-7B and DeepSeek-V4-Pro using the same provider-sourced text & reasoning rubric. No mystery score and no invented benchmark ranking.
Facts checked September 4, 2026
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.
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) |
|---|---|---|
| DeepSeek-V4-ProDeepSeek | DeepSeek | No reviewed rate |
| Falcon-H1R-7BTechnology Innovation Institute | Technology Innovation Institute | No reviewed rate |
Quick take
TII's compact open reasoning model for text tasks, long contexts, and self-hosted function-calling workflows.
A long advertised context can consume far more memory than a normal 8K request. Validate quality and capacity at your actual context length rather than sizing from parameter count alone.
DeepSeek's flagship million-context text model for difficult reasoning, coding, long-running agents, tools, and very large outputs.
The provider does not publish a knowledge cutoff or a universal speed measure. Review jurisdiction, account eligibility, cache behavior, data terms, and the full reasoning-output cost before sending sensitive workloads.
Compare the published facts
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 | Falcon-H1R-7B | DeepSeek-V4-Pro |
|---|---|---|
| Context windowMaximum combined prompt and working context documented by the provider. | Up to 262K in documented vLLM setup | 1M tokens |
| Maximum outputProvider-published response limit, where available. | Up to 65,536 recommended | Up to 384K tokens |
| 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. | Self-hosted compute | $1.32 / 1M peak uncached; $0.66 off-peak |
| Output priceCurrent standard list price per million output tokens unless noted. | Self-hosted compute | $3.96 / 1M peak; $1.98 off-peak |
| InputsMedia types accepted by the listed model endpoint. | Text | Text |
| Tools & agentsSelected native tools and agent-building capabilities, not an exhaustive list. | Function calling through supported serving templates | Tools, JSON output, Responses API, thinking effort, FIM beta |
How to choose
Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.
Self-hosted inference keeps requests under the operator's own infrastructure and data controls. A third-party host can introduce separate logging, retention, and training terms.
Provider and API links
DeepSeek documents its Responses API as stateless and says responses and conversations are not stored by that endpoint. This is not a complete account-wide retention or training-use promise; review current platform terms and automatic cache behavior for sensitive data.
Provider and API links
Frequently asked questions
Falcon-H1R-7B: TII's compact open reasoning model for text tasks, long contexts, and self-hosted function-calling workflows. DeepSeek-V4-Pro: DeepSeek's flagship million-context text model for difficult reasoning, coding, long-running agents, tools, and very large outputs.
Consider Falcon-H1R-7B when your priority is Private reasoning assistants. Consider DeepSeek-V4-Pro when your priority is Complex coding and tool-using agents. Test both with your own data and provider route before committing.
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.
