DeepSeek vs Llama 4 — Reasoning & Cost Comparison

DeepSeek vs Llama 4: which open-weight champion?

DeepSeek and Llama 4 are both open-weight models built for serious reasoning and coding work. DeepSeek is faster and dramatically cheaper per token; Llama 4 brings a mature fine-tuning ecosystem and a permissive commercial license. For most Indian teams the default is DeepSeek — but Llama earns its place for specific workloads.

Detailed comparison

Metric	DeepSeek V4 Flash	Llama 4 Scout
Input cost (₹/1M)	₹9.11	₹10.12
Output cost (₹/1M)	₹18.21	₹30.36
Reasoning (math/logic)	Excellent	Fair
Coding quality	Excellent	Good
Context window	About 1M	About 327K
Weights public	Yes	Yes
Commercial fine-tuning	Requires local infra	Meta license, widely supported

Rates as of 6 October 2026; the live price is on each model page. (Llama 4 Maverick is not currently offered on unoblox.)

When to use DeepSeek

• Budget-first projects: ₹9.11 input is among the lowest rates on unoblox for a model of this class.
• Reasoning-heavy apps: math, physics, and finance calculations are where DeepSeek's pipeline is strongest.
• High API volume: millions of small completions keep DeepSeek's per-token economics decisively ahead.
• Edge deployment: run it locally for zero added latency, with unoblox as the managed fallback.

When to use Llama 4

• Fine-tuning your own domain model: Meta's license explicitly allows commercial fine-tuning — train Llama on your data and self-host the result.
• Tight secondary budget: Llama 4 Scout at ₹10.12 input is close to DeepSeek's price and still capable for straightforward tasks.
• Community tooling: a large ecosystem of adapters, quantizations, and deployment guides around Llama makes ops easier.
• On-prem or data-residency needs: run entirely on your own infrastructure when that's a hard requirement, not just a preference.

Cost example: 100M input + 20M output tokens a month

Model	Input cost	Output cost	Total
DeepSeek V4 Flash	₹911.00	₹364.20	₹1,275.20
Llama 4 Scout	₹1,012.00	₹607.20	₹1,619.20

DeepSeek is roughly 21% cheaper than Scout at this volume — the gap widens further as output tokens grow.

Frequently asked questions

Is Llama 4 open enough for my needs? Yes — weights are fully open under Meta's license. Download from Meta's repository and run locally with vLLM, SGLang, or similar.

Can I fine-tune Llama on unoblox? unoblox serves inference only. Fine-tune Llama on your own infrastructure or a training service, then run inference on the result yourself, or serve the base model through unoblox instead.

Does DeepSeek ship official open weights? Yes, DeepSeek releases its weights under a permissive license alongside the hosted API.

What's the production SLA on unoblox? 99.95% uptime across all models, DeepSeek and Llama included.

Which is better for Indian languages? Both handle Hindi, Tamil, and Telugu adequately. If Indic-language quality is the priority, Qwen3 generally does better than either.

Can I route between all three models automatically? Yes — one API key covers DeepSeek and Llama 4 Scout, so you can route by task complexity in your own application logic.

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