# The Multivac — Evaluation Report

**Evaluation ID:** EVAL-20260207-150152
**Date:** Jan 15, 2026
**Category:** communication
**Question ID:** COMM-001

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## Question

Explain how transformer neural networks work. Provide two explanations:

1. For a junior software developer who knows basic Python but has no ML background
2. For a senior ML engineer who knows CNNs/RNNs but hasn't worked with transformers

Both explanations should be technically accurate. The first should build intuition; the second should highlight architectural innovations.

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## Winner

**Seed 1.6 Flash** (ByteDance)
- Winner Score: 9.68
- Matrix Average: 8.41
- Total Judgments: 90

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## Rankings

| Rank | Model | Provider | Avg Score | Judgments |
|------|-------|----------|-----------|----------|
| 1 | Seed 1.6 Flash | ByteDance | 9.68 | 9 |
| 2 | Mistral Small Creative | Mistral | 9.62 | 8 |
| 3 | Claude Sonnet 4.5 | Anthropic | 9.51 | 8 |
| 4 | Grok 4.1 Fast | xAI | 9.41 | 8 |
| 5 | DeepSeek V3.2 | DeepSeek | 9.13 | 8 |
| 6 | Claude Opus 4.5 | Anthropic | 9.11 | 8 |
| 7 | GPT-OSS-120B | OpenAI | 8.86 | 9 |
| 8 | Gemini 2.5 Flash | Google | 8.69 | 7 |
| 9 | GLM-4-7 | Zhipu | 7.20 | 8 |
| 10 | Gemini 2.5 Flash Lite | Google | 2.89 | 7 |

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## 10×10 Judgment Matrix

Rows = Judge, Columns = Respondent. Self-judgments excluded (—).

| Judge ↓ / Resp → | Seed 1.6 Flash | Gemini 2.5 | GLM-4-7 | Gemini 2.5 | GPT-OSS-120B | Grok 4.1 Fast | DeepSeek V3.2 | Claude Sonnet | Claude Opus | Mistral Small |
|---|---|---|---|---|---|---|---|---|---|---|
| Seed 1.6 Flash | — | 1.3 | 7.0 | 8.3 | 9.0 | 9.0 | 8.7 | 9.2 | 9.0 | 9.3 |
| Gemini 2.5 | 10.0 | — | 8.4 | 9.3 | 9.8 | 10.0 | 9.3 | 10.0 | 9.4 | 10.0 |
| GLM-4-7 | 9.6 | 0.2 | — | 0.0 | 7.0 | 9.6 | 8.6 | 9.6 | 0.0 | 0.0 |
| Gemini 2.5 | 10.0 | 0.0 | 8.6 | — | 9.0 | 9.6 | 9.6 | 9.6 | 9.6 | 10.0 |
| GPT-OSS-120B | 8.8 | 3.5 | 5.0 | 6.9 | — | 9.0 | 8.6 | 9.0 | 7.7 | 8.8 |
| Grok 4.1 Fast | 10.0 | 4.3 | 6.4 | 9.4 | 8.8 | — | 9.8 | 10.0 | 9.4 | 10.0 |
| DeepSeek V3.2 | 9.6 | 1.6 | 7.3 | 9.0 | 9.0 | 9.6 | — | 9.3 | 8.8 | 10.0 |
| Claude Sonnet | 9.8 | 0.0 | 8.4 | 9.8 | 9.0 | 9.2 | 9.3 | — | 9.0 | 9.6 |
| Claude Opus | 9.3 | 1.6 | 6.3 | 8.3 | 8.1 | 9.3 | 9.2 | 9.3 | — | 9.3 |
| Mistral Small | 10.0 | 7.6 | 0.0 | 0.0 | 10.0 | 0.0 | 0.0 | 0.0 | 10.0 | — |

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## Methodology

- **10×10 Blind Peer Matrix:** All models answer the same question, then all models judge all responses.
- **5 Criteria:** Correctness, completeness, clarity, depth, usefulness (each scored 1–10).
- **Self-judgments excluded:** Models do not judge their own responses.
- **Weighted Score:** Composite of all 5 criteria.

---

## Citation

The Multivac (2026). Blind Peer Evaluation: COMM-001. app.themultivac.com

## License

Open data. Free to use, share, and build upon. Please cite The Multivac when using this data.

Download raw JSON: https://app.themultivac.com/api/evaluations/EVAL-20260207-150152/results
Full dataset: https://app.themultivac.com/dashboard/export