Use the new version of deepseek r1 0528 here.
| Feature | DeepSeek R1-0528 | Why It Matters |
|---|---|---|
| Context window | 128 K tokens (real-world recall ≈ 32–64 K) | Summarise whole books or codebases |
| Model size | 671 B total / 37 B active (MoE) | Frontier reasoning on mid-range clusters |
| LiveCodeBench | 73.1 Pass@1 – #4 overall | Beats Grok 3 Mini & Qwen 3 |
| Token cost | $0.014 per 5 K-token chat | ~92 % cheaper than GPT-4o |
| Red-team fail rate | 91 % jailbreak, 93 % malware | Highest risk among top models |
Why This “Minor” Upgrade Shook the Leaderboards
DeepSeek’s engineers dropped R1-0528 onto Hugging Face on 28 May 2025 with no fanfare. Within three days it:
- Overtook Grok 3 Mini on LiveCodeBench.
- Triggered Google and OpenAI to slash certain API prices.
- Re-ignited U.S. House hearings on CCP tech influence.
DeepSeek calls it a trial upgrade—but the numbers say otherwise.
Under the Hood: 671 B Parameters on a Diet
Mixture of Experts (MoE)
Only 5 % of weights fire per token (37 B of 671 B), giving near-GPT-4 logic without GPT-4 bills.
FP8 + Multi-Token Prediction
- FP8 math cuts VRAM 75 % versus FP32.
- 8-token decoding halves latency at long contexts.
Chain-of-Thought Training
Reinforcement Learning with Group Relative Policy Optimisation (GRPO) pushes the model to think in explicit steps—then prints those steps between <think> tags (great for debugging, disastrous for secrets).
Benchmark Showdown
Code Generation (LiveCodeBench v1.1)
| Rank | Model | Pass@1 |
|---|---|---|
| 1 | OpenAI o4 Mini (High) | 80.2 |
| 2 | OpenAI o3 (High) | 75.8 |
| 3 | OpenAI o4 Mini (Med) | 74.2 |
| 4 | DeepSeek R1-0528 | 73.1 |
| 5 | OpenAI o3 Mini (High) | 67.4 |
| 6 | xAI Grok 3 Mini (High) | 66.7 |
| 8 | Alibaba Qwen 3-235B | 65.9 |
Take-away: only OpenAI’s top-tier models beat it—and they cost 5-10× more.
Math & Logic
Original R1 hit 97.3 % on MATH-500. Early tests show 0528 edging closer to OpenAI o3-level reasoning.
Red-Team Stress
| Attack Vector | Fail Rate* |
|---|---|
| Jailbreak prompts | 91 % |
| Malware generation | 93 % |
| Prompt injection | 86 % |
| Toxic output | 68 % |
*PointGuard AI, May 2025. Highest among mainstream LLMs.
Deploy-or-Avoid Guide
Access Paths
| Route | Context | Cost | Best For |
|---|---|---|---|
| OpenRouter API | 164 K* | $0.50 / M in, 2.18 out | Rapid prototyping |
| Fireworks AI | 32 K | Similar | Fine-tuned LoRA |
| Local GGUF 4-bit | 32–64 K | Hardware only | Data-sensitive orgs |
*Higher than spec; real recall varies.
Hardening Checklist
- Strip
<think>before logs/UI. - Wrap replies with OpenAI Moderation or AWS Guardrails.
- Enforce rate-limits & max-tokens.
- Isolate secrets; never embed keys in prompts.
- Verify GGUF SHA-256; avoid rogue forks.
Cost Math
- 5 K-token dialog (in + out): $0.014 (R1-0528) vs $0.18 (GPT-4o).
- At 1M tokens/month you’d bank $332 savings.
Censorship, Data Flow & Geopolitics
- House CCP report: traffic routes via China Mobile; 85 % of democracy queries softened or blocked.
- NASA, U.S. Navy, Tennessee ban DeepSeek on official devices.
- Android app audited with hard-coded AES keys and SQL-injection flaws.
Bottom line: treat cloud access as off-limits for regulated or PII data.
Where Does It Beat—and Lose to—GPT-4o?
| Task | Winner | Why |
|---|---|---|
| Long-doc summarisation | R1-0528 | 2–4× larger working memory |
| Raw coding Pass@1 cost | R1-0528 | 90 % cheaper |
| Hallucination control | GPT-4o | Better refusal heuristics |
| Safety compliance | GPT-4o | Lower malware, toxicity |
| Political neutrality | GPT-4o | No CCP alignment |
Roadmap: Eyes on DeepSeek R2
Rumoured Q3 2025 launch promises:
- Multimodal I/O (text + image + audio).
- Generative Reward Modelling for self-feedback.
- Target: GPT-4o parity at half the compute.
If DeepSeek keeps the price edge and patches security, the market could tip.
Practical Use Cases Today
- Indie devs: generate boiler-plate React or Unity scripts fast.
- Academics: ingest full papers (≤ 60 K tokens) for meta-analysis.
- Legal ops: rapid first-pass contract review—locally hosted only.
- Game masters: rich lore consistency over giant campaign notes.
Expert Insight
“R1-0528 is the first free model that lets me paste a whole 400-page PDF and ask nuanced questions. But I sandbox it—its<think>tag once spilled an AWS key.”
—CTO, mid-size SaaS (name withheld)
FAQs
Does the 128 K context actually work?
Recall stays sharp to ~32 K; coherence fades beyond 64 K.
Can I fine-tune on a single A100?
Yes—4-bit QLoRA < 48 GB VRAM.
Is the MIT license truly commercial-friendly?
Yes, but it bars using outputs to train a competing model.
How to disable political filters?
Only via jailbreak prompts—raises legal & ethical flags.
Key Takeaway
DeepSeek R1-0528 brings near-GPT-4 logic and 128 K memory at bargain prices—but with the highest jailbreak rates on record. Use it where cost wins, sandbox it where reputation matters, and watch the coming R2 raise the stakes yet again.