DeepSeek-V3.1 vs Blackbox E2E Encrypted (Pro)
Compare the listed model data for DeepSeek-V3.1 by DeepSeek and Blackbox E2E Encrypted (Pro) by Blackbox AI. Benchmark and pricing records are not a controlled test and may change.
Data last updated: 2026-10-16. Verify current model details with each provider.
What the listed data says
DeepSeek-V3.1: 128K tokens; Blackbox E2E Encrypted (Pro): 128K tokens. The listed context-window values are equal. DeepSeek-V3.1 is listed for no specific capability flags; Blackbox E2E Encrypted (Pro) is listed for coding, reasoning, long-context tasks. Shared catalog benchmark entries: MMLU: DeepSeek-V3.1 91.7%; Blackbox E2E Encrypted (Pro) 81.4%; HumanEval: DeepSeek-V3.1 93.8%; Blackbox E2E Encrypted (Pro) 83.1%. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
Catalog source links
Use these model and provider links to verify current specifications, pricing, and availability.
Computed differences from catalog data
- The listed context windows are 128K tokens and 128K tokens; the larger is 1× the smaller.
- On shared numeric benchmark entries, MMLU: DeepSeek-V3.1 − Blackbox E2E Encrypted (Pro) = +10.3 percentage points (91.7% vs 81.4%); HumanEval: DeepSeek-V3.1 − Blackbox E2E Encrypted (Pro) = +10.7 percentage points (93.8% vs 83.1%).
- The first listed parameter quantities are 671B total (37B active via MoE) and ~70B (proprietary, encrypted inference); the larger quantity is 9.59× the smaller. Total and active MoE parameters are not directly equivalent.
- A release-date gap cannot be calculated from the catalog values (DeepSeek-V3.1: June 2025; Blackbox E2E Encrypted (Pro): 2025).
Cost example: 1M input and 1M output tokens
A cost example for 1M input plus 1M output tokens cannot be calculated reliably because separate numeric input and output rates are not listed for both models.
Choose DeepSeek-V3.1 if…
Choose DeepSeek-V3.1 when your task aligns with catalog-listed uses or strengths such as Enterprise software development requiring high quality at low latency, Document intelligence and knowledge base applications, API providers serving general business customers, DeepSeek's most capable non-reasoning model as of June 2025.
Choose Blackbox E2E Encrypted (Pro) if…
Choose Blackbox E2E Encrypted (Pro) when your task aligns with catalog-listed uses or strengths such as Sensitive source code generation where IP confidentiality is critical, Healthcare AI applications handling protected health information (PHI), Legal document drafting where attorney-client privilege demands confidentiality, Financial modeling and trading strategy development requiring data privacy.
DeepSeek-V3.1
DeepSeek-V3.1 — next iteration with improved instruction following, better coding, and stronger general capabilities.
Parameters: 671B total (37B active via MoE)
Context: 128K tokens
Catalog pricing: MIT open source. DeepSeek API: ~$0.27/MTok input, ~$1.10/MTok output
Blackbox E2E Encrypted (Pro)
Blackbox E2E Encrypted — privacy-first AI model with end-to-end encryption. Ideal for sensitive code, confidential analysis, and private workflows.
Parameters: ~70B (proprietary, encrypted inference)
Context: 128K tokens
Catalog pricing: Via LITHOVEX AI free for basic use
Feature Comparison — DeepSeek-V3.1 vs Blackbox E2E Encrypted (Pro)
| Specification | DeepSeek-V3.1 | Blackbox E2E Encrypted (Pro) |
|---|---|---|
| Provider | DeepSeek | Blackbox AI |
| Parameters | 671B total (37B active via MoE) | ~70B (proprietary, encrypted inference) |
| Context window | 128K tokens | 128K tokens |
| Maximum output | Not listed | Not listed |
| Catalog pricing | MIT open source. DeepSeek API: ~$0.27/MTok input, ~$1.10/MTok output | Via LITHOVEX AI free for basic use |
| Listed input/output cost per 1M tokens | Separate numeric input/output rates not listed | Separate numeric input/output rates not listed |
| License | MIT | Proprietary |
| Coding support | Not listed | Listed |
| Reasoning support | Not listed | Listed |
| Vision input | Not listed | Not listed |
| Multimodal | Not listed | Not listed |
| Open weights | Yes | No |
| Benchmark: MMLU | 91.7% | 81.4% |
| Benchmark: HumanEval | 93.8% | 83.1% |
Figures are transcribed from LITHOVEX model records. Benchmark versions and evaluation setups may differ; pricing and specifications can change. Check each provider's current documentation before making a decision.
Frequently Asked Questions
What is different between DeepSeek-V3.1 and Blackbox E2E Encrypted (Pro)?
What benchmark values are listed for DeepSeek-V3.1 and Blackbox E2E Encrypted (Pro)?
Which model has the larger listed context window?
What are the listed costs per million tokens for DeepSeek-V3.1 and Blackbox E2E Encrypted (Pro)?
How far apart are the listed release dates for DeepSeek-V3.1 and Blackbox E2E Encrypted (Pro)?
When was the comparison data last updated?
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Explore these models and related comparisons
Read the DeepSeek-V3.1 model profile and Blackbox E2E Encrypted (Pro) model profile, or browse the model directory.