pith:CSY654CR
Phi-4-reasoning Technical Report
A 14-billion parameter model trained on curated teachable prompts and o3-mini demonstrations reaches performance levels of much larger reasoning systems.
arxiv:2504.21318 v1 · 2025-04-30 · cs.AI · cs.CL
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Claims
Across a wide range of reasoning tasks, both models outperform significantly larger open-weight models such as DeepSeek-R1-Distill-Llama-70B model and approach the performance levels of full DeepSeek-R1 model.
That the performance improvements stem primarily from the curated 'teachable' prompts and o3-mini demonstrations rather than from undisclosed details of the base Phi-4 model, evaluation choices, or overlap with the teacher model's training data.
A 14B reasoning model trained via supervised fine-tuning on selected prompts and o3-mini traces, plus outcome RL, outperforms larger open models like DeepSeek-R1-Distill-Llama-70B on math, coding, planning and related benchmarks.
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Receipt and verification
| First computed | 2026-05-17T23:38:15.236139Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519 (pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
14b1eef051b0fdc721e5ce976bbe56168c5f4b9b3db39f240432fa7349969614
Aliases
· ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/CSY654CRWD64OIPFZ2LWXPSWC2 \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 14b1eef051b0fdc721e5ce976bbe56168c5f4b9b3db39f240432fa7349969614
Canonical record JSON
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