DeepSeek V3.2 vs Llama 4 Maverick
Compare DeepSeek and Meta (via Together AI) AI models
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
DeepSeek V3.2
Llama 4 Maverick
Cost Differences
Llama 4 Maverick costs more than DeepSeek V3.2
Feature Comparison
| Feature | DeepSeek V3.2 | Llama 4 Maverick |
|---|---|---|
| Provider | DeepSeek | Meta (via Together AI) |
| Input Price | $0.28/1M tokens | $0.27/1M tokens |
| Output Price | $0.42/1M tokens | $0.85/1M tokens |
| Context Window | 128,000 tokens | 1,000,000 tokens |
| Max Output | 32,768 tokens | 65,536 tokens |
| Category | efficient | flagship |
| Capabilities | textcodereasoning | textvisioncode |
| Release Date | 12/1/2025 | 4/5/2025 |
DeepSeek V3.2 vs Llama 4 Maverick: Which Should You Choose?
Choosing between DeepSeek V3.2 and Llama 4 Maverick depends on your priorities: cost efficiency, context length, or raw capability. DeepSeek V3.2 is the more affordable option at $0.28/1M input tokens. Meanwhile, Llama 4 Maverick offers a significantly larger context window at 1,000,000 tokens vs 128,000 for DeepSeek V3.2.
These models come from different providers — DeepSeek and Meta (via Together AI) — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with DeepSeek, switching to Meta (via Together AI)involves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
These models target different tiers: DeepSeek V3.2 is a efficient model while Llama 4 Maverick is flagship. This means they're optimized for different workloads. Llama 4 Maverick targets more demanding workloads, while DeepSeek V3.2 provides a cost-effective option for everyday tasks.
Output costs matter too. DeepSeek V3.2 charges $0.42/1M output tokens vs $0.85 for Llama 4 Maverick. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. DeepSeek V3.2 has the edge here at $0.42/1M output tokens.
Multimodal capabilities: Llama 4 Maverick supports vision (image inputs) while DeepSeek V3.2 is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
Choose DeepSeek V3.2 when:
- • You're already using DeepSeek's API ecosystem
- • You're running high-volume, latency-sensitive workloads
Choose Llama 4 Maverick when:
- • Budget is a primary concern
- • You need a larger context window (1,000,000 tokens)
- • You need longer outputs (up to 65,536 tokens)
- • You're already using Meta (via Together AI)'s API ecosystem
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
DeepSeek V3.2 (DeepSeek)
Llama 4 Maverick (Meta (via Together AI))
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