DeepSeek V4 Pro vs Llama 4 Maverick
Two open-source heavyweights. DeepSeek V4 Pro is 61% cheaper on input with slightly higher output pricing. Both have 1M context windows. See which fits your workload.
Pricing data verified: 2026-06-20
| Specification | DeepSeek V4 Pro (DeepSeek) | Llama 4 Maverick (Meta) |
|---|---|---|
| Input Price (per 1M tokens) | $0.435 | $0.27 |
| Output Price (per 1M tokens) | $0.87 | $0.85 |
| Context Window | 1M | 1M |
| Tier | Budget | Budget |
| Provider | DeepSeek | Meta (Together.ai) |
Calculate Your Exact Costs
See how the costs stack up for your specific usage pattern.
Other Models to Consider
Which Model for Which Use Case?
Cost-Sensitive High Volume
DeepSeek V4 Pro's $0.435/M input is 61% cheaper than Llama's $0.27/M — wait, actually Llama is cheaper on input. For input-heavy workloads, Llama 4 Maverick saves more.
Coding & Math
DeepSeek V4 Pro consistently benchmarks higher on coding tasks and mathematical reasoning. If code generation or analysis is your primary use case, DeepSeek is the better pick.
Multilingual & Creative
Llama 4 Maverick is trained on more diverse multilingual data and tends to produce more creative, natural-sounding text across languages.
Self-Hosting
Both are open-source. DeepSeek V4 Pro is generally more efficient to run (fewer parameters for similar performance). Llama 4 Maverick has broader community support and tooling.
Comparing Open-Source Models?
APIpulse Pro lets you compare all 42 models, find the cheapest option for your exact usage, and save scenarios for your team.
Frequently Asked Questions
Is DeepSeek V4 Pro cheaper than Llama 4 Maverick?
DeepSeek V4 Pro costs $0.435/M input and $0.87/M output. Llama 4 Maverick costs $0.27/M input and $0.85/M output. Llama is cheaper overall — 38% cheaper on input and 2% cheaper on output.
Which open-source model has better quality?
DeepSeek V4 Pro generally benchmarks higher on coding, math, and reasoning tasks. Llama 4 Maverick is stronger on multilingual and creative tasks. Both are competitive for most use cases.
Which model has a larger context window?
Both DeepSeek V4 Pro and Llama 4 Maverick have 1M token context windows — equally large for handling long documents and complex conversations.
Can I self-host these models?
Yes, both are open-source. DeepSeek V4 Pro and Llama 4 Maverick can be self-hosted. Self-hosting costs vary by hardware — DeepSeek is generally more efficient to run.