DeepSeek just launched V4-Pro and V4-Flash — live on Hugging Face, MIT licensed, free to download. Codeforces rating 3206. SWE Verified 80.6%. Apex Shortlist 90.2%. API at ₹25 per million tokens vs ₹420 for Claude. This article includes the complete official benchmark table from DeepSeek’s technical report.
Ahmedabad / Bengaluru, April 24, 2026 — Exactly 484 days after DeepSeek V3 shocked Silicon Valley, DeepSeek has done it again. At 3:00 AM IST this morning, DeepSeek posted the launch on X. Within the hour, the weights were on Hugging Face, the API was live, and the complete technical report was public. This article gives you everything — the model specs, the full official benchmark table, the pricing, and exactly what Indian developers should do right now.
📌 Source Verification
All benchmark numbers in this article are sourced directly from DeepSeek’s official technical report (PDF, Hugging Face), DeepSeek’s official X announcement (@deepseek_ai, April 24, 2026), and the official Hugging Face model card. Corroborated by Bloomberg and OfficeChai within the first hour of launch. Every number in the benchmark table below comes from DeepSeek’s own published evaluation — not third-party estimates.
The Two Models — Official Specs
V4-Pro is a Mixture-of-Experts model — 1.6 trillion total parameters but only 49 billion active on any given token. This MoE architecture is what makes it efficient enough to train under chip restrictions and cheap enough to serve at ₹25 per million tokens. V4-Flash is the practical everyday model — same 1 million token context, same MIT license, a fraction of the compute requirement. Both support thinking and non-thinking modes, JSON output, Tool Calls, and Chat Prefix Completion (Beta). Both are available now via OpenAI-compatible and Anthropic-compatible API endpoints.
The Complete Official Benchmark Table
DeepSeek published a full benchmark table in their technical report comparing V4-Pro Max and V4-Flash Max against Claude Opus 4.6 Max, GPT-5.4 xHigh, K2.6 Thinking, GLM-5.1 Thinking, and Gemini-3.1-Pro High. This is the most complete benchmark comparison available anywhere for DeepSeek V4. Every number below is from the official DeepSeek technical report published today.
🟢 Green = leads in that benchmark · Source: DeepSeek V4 Official Technical Report, April 24, 2026
Reading the Benchmarks Honestly — Where V4 Wins and Where It Doesn’t
This is the section most AI coverage skips. DeepSeek’s technical report is unusually transparent — they show wins and losses side by side. Here is the honest summary:
Where DeepSeek V4-Pro Clearly Leads
- Codeforces Rating: 3206 — highest of any model in the comparison, beating GPT-5.4 (3168) and Gemini (3052). This is the most prestigious competitive coding benchmark in the world. V4-Pro is now ranked #1 among all frontier models on it.
- LiveCodeBench: 93.5 — beats Claude (88.8) and Gemini (91.7). GPT-5.4 score not disclosed.
- Apex Shortlist: 90.2 — beats Claude (85.9), GPT-5.4 (78.1), and Gemini (89.1).
- IMOAnswerBench: 89.8 — strong math, beats Claude (75.3) and Gemini (81.0), trails only GPT-5.4 (91.4).
- Chinese-SimpleQA: 84.4 — leads all non-Chinese models.
- SWE Verified: 80.6 — matches Gemini (80.6), just below Claude (80.8). Real-world software engineering benchmark.
- MCPAtlas Public: 73.6 — leads all models including Claude (73.8 — essentially tied).
Where V4-Pro Trails — Be Honest With Your Readers
- MRCR 1M (Long Context): 83.5 — Claude leads significantly at 92.9. For very long document tasks, Claude remains stronger.
- MMLU-Pro: 87.5 — Gemini leads at 91.0. General academic knowledge is not V4’s strongest area.
- GPQA Diamond: 90.1 — GPT-5.4 (93.0) and Gemini (94.3) lead. Scientific reasoning gap exists.
- HLE: 37.7 — trails Claude (40.0), GPT-5.4 (39.8), and especially Gemini (44.4).
- Terminal Bench 2.0: 67.9 — GPT-5.4 leads at 75.1. Terminal-heavy workflows are not V4’s best use case.
- GDFVal-AA: 1554 — GPT-5.4 leads at 1674, Claude at 1619.
- Apex: 38.3 — trails GPT-5.4 (54.1) and Gemini (60.9) significantly.
⚠️ The Honest Verdict
DeepSeek V4-Pro is the best open-source model ever released and is genuinely competitive with GPT-5.4 on coding and math. It is not the best model overall. Gemini-3.1-Pro leads on general knowledge and HLE. GPT-5.4 leads on terminal tasks, Apex, and scientific reasoning. Claude Opus 4.6 leads on long-context tasks. For Indian developers choosing between models: if you are building coding tools, V4-Pro is world-class. If you are building knowledge-retrieval or long-document applications, test Claude or Gemini alongside it before committing.
The Price That Changes Everything
Here is the number that matters most for Indian developers. V4-Pro API pricing is $0.30 per million input tokens / $0.50 per million output tokens — approximately ₹25 per million input tokens.
One developer who ran production workloads on DeepSeek reported: the same workload cost $18/month on DeepSeek vs $380 on GPT-4o and $720 on Claude Opus 4.5. The gap has not narrowed with V4. It has stayed the same — which means frontier-class capability at Indian startup-friendly pricing is now a reality, not a tradeoff.
And if you want to eliminate API costs entirely: the open weights under MIT license mean you can self-host V4-Flash for free. A server with dual RTX 4090 GPUs handles smaller workloads with zero ongoing cost. No other frontier-competitive model offers this.
The Huawei Chip Story — Why This Matters Beyond AI
DeepSeek V4 was trained on Huawei’s Ascend 950PR chips — confirmed by Reuters on April 4 and now validated by the actual launch. The US has spent two years implementing chip export restrictions to prevent Chinese AI labs from training frontier models. DeepSeek V4 is a direct empirical refutation of that logic.
🔵 The Geopolitical Signal
A Chinese company under hardware restrictions trained the world’s best open-source coding model. This invalidates the compute-restriction theory of AI competition, puts pressure on NVIDIA’s moat, and confirms that open-source AI now competes with closed-source frontier models in real time — not in the future. As one X user noted: “A Chinese company facing chip restrictions can train this. But xAI can’t even get SOTA with a million H100 equivalents.” That observation cuts deep.
Three India Angles That Matter Right Now
1. ₹25 Per Million Tokens — The Indian Startup Unlock
India has over 3 million developers using AI tools regularly. At ₹420 per million tokens for Claude Opus or ₹210 for GPT-5.4, high-volume applications are prohibitively expensive for most Indian startups. DeepSeek V4-Pro at ₹25 per million tokens, or V4-Flash self-hosted for free, changes the economics of building AI products in India entirely. Startups that were rationing AI calls can now build without counting tokens.
2. Codeforces 3206 — The India Developer Angle
India produces more competitive programmers per year than almost any other country. Codeforces is the benchmark those developers understand and respect. V4-Pro scoring 3206 — above GPT-5.4 at 3168 and Gemini at 3052 — is a number Indian developers will immediately grasp as significant. This is not a research benchmark. It is competitive programming. The model is genuinely good at the kind of algorithmic problem-solving that Indian CS graduates are trained on.
3. Zero Migration Cost
DeepSeek V4 is available immediately via OpenAI-compatible and Anthropic-compatible API endpoints. Any Indian startup running on the OpenAI API can switch to V4-Pro by changing one line of code. Migration time: approximately ten minutes. Cost saving: approximately 88%.
✅ How to Access Right Now
Web: chat.deepseek.com → Expert Mode (V4-Pro) or Instant Mode (V4-Flash)
Download weights (free): huggingface.co/collections/deepseek-ai/deepseek-v4
API: Available now — OpenAI-compatible and Anthropic-compatible endpoints
Technical report: huggingface.co/deepseek-ai/DeepSeek-V4-Pro/blob/main/DeepSeek_V4.pdf
Free tier: 5 million free tokens for new API accounts (~₹125 value) — no credit card required
License: MIT — fully commercial, modify freely, use forever at no cost
Important Caveats Before You Migrate Production
- Preview release: Run your own evaluations on your specific use case before migrating production workloads. Preview releases can have rough edges.
- Long context caution: The benchmark data shows Claude Opus 4.6 leads significantly on MRCR 1M (92.9 vs 83.5). For applications heavily dependent on retrieving information from very long documents, test carefully before assuming V4 matches Claude.
- API rate limits at launch: High launch-day demand means rate limiting is likely. V4-Flash may be more reliably accessible while V4-Pro capacity scales up.
- Data privacy for enterprises: DeepSeek is a Chinese company subject to Chinese data laws. For Indian enterprises handling sensitive healthcare, financial, or government data, self-hosting the open weights on Indian infrastructure eliminates this concern entirely.
- Independent benchmark verification: All benchmarks come from DeepSeek’s own technical report. Third-party independent verification takes days to weeks. The numbers are consistent with DeepSeek’s track record from V3, but verify for your specific use case.
484 Days — The Bigger Story
DeepSeek team member Deli Chen posted one sentence alongside the launch: “DeepSeek-V3: Dec 26, 2024. DeepSeek-V4: Apr 24, 2026. 484 days later, we humbly share our labor of love. As always, we stay true to long-termism and open source for all. AGI belongs to everyone.”
In those 484 days, OpenAI went from GPT-4 to GPT-5.4. Anthropic built Opus 4.7 and the restricted Mythos Preview. Amazon committed 5 gigawatts of compute to Anthropic three days ago. The compute available to Western labs exploded. DeepSeek built a model that beats GPT-5.4 on Codeforces and matches it on SWE Verified — using Huawei chips.
For Indian developers: the era of frontier AI being a closed, expensive, Western-only product is over. It ended this morning. A Codeforces 3206 model is free to download. A 1M context coding assistant costs ₹25 per million tokens. You can self-host it on your own servers for nothing.
Whether that inspires you or overwhelms you, it is the reality. Act accordingly.
FAQs
Is DeepSeek V4 really free to use?
Yes. DeepSeek V4-Flash weights are free to download from Hugging Face under MIT license — meaning free to use, modify, and deploy commercially. The API has a free tier of 5 million tokens for new accounts with no credit card required. V4-Pro API costs ₹25 per million input tokens.
Can Indian developers switch from ChatGPT to DeepSeek V4 easily?
Yes — in about 10 minutes. DeepSeek V4 supports OpenAI-compatible API endpoints, meaning you change one line of code. No SDK change, no rewriting prompts. Cost saving is approximately 88% vs GPT-5.4.
Is DeepSeek V4 better than Claude and GPT-5.4?
For coding tasks — yes. V4-Pro scores Codeforces 3206, ranking #1 globally above GPT-5.4 (3168). However Claude Opus 4.6 leads on long-context tasks and Gemini-3.1-Pro leads on general knowledge. V4-Pro is the best choice for coding and math. Not the best model for everything.
Primary sources: DeepSeek official X @deepseek_ai (April 24, 2026) · DeepSeek V4 Technical Report PDF (Hugging Face, April 24, 2026) · Hugging Face model card: deepseek-ai/DeepSeek-V4-Pro · Bloomberg (April 24, 2026) · OfficeChai benchmark analysis (April 24, 2026) · Reuters Huawei chip confirmation (April 4, 2026) · WaveSpeedAI pricing breakdown.
⚠️ Benchmark disclaimer: All figures sourced from DeepSeek’s own technical report. Independent third-party verification is ongoing. Run your own evaluations before committing to production migration. This is a preview release.