DeepSeek: DeepSeek V4 Flash (DeepSeek) ile Meta: Llama 4 Maverick (Meta) modellerini fiyat, baglam, yetenekler ve gecikme acisindan karsilastirin.
Yan yana
Fiyat, saglayici, baglam, yetenekler, gecikme ve kaynak temelini karsilastirin.
| Model | Provider | Input | Output | Context | Capabilities | Best for | Latency | Status | Source |
|---|---|---|---|---|---|---|---|---|---|
| DeepSeek: DeepSeek V4 Flashdeepseek/deepseek-v4-flash | DeepSeek | $0.112 / 1M tokens | $0.224 / 1M tokens | 1M | Tool callingJSON modeLong contextReasoning | low-cost Chinese tasks, long-context summary | 800-2600ms | Catalog | OpenRouter if available |
| Meta: Llama 4 Maverickmeta-llama/llama-4-maverick | Meta | $0.15 / 1M tokens | $0.6 / 1M tokens | 1M | JSON modeLong contextStreamingLow cost | open-model workflows, cost-sensitive long context | 950-2800ms | Catalog | OpenRouter if available |
FAQ
DeepSeek: DeepSeek V4 Flash, Meta: Llama 4 Maverick modeline gore daha ucuzdur ($0.112 / 1M tokens input / $0.224 / 1M tokens output vs $0.15 / 1M tokens input / $0.6 / 1M tokens output). Gercek maliyet, giris ve cikis token karisiminiza baglidir; bu nedenle fiyat hesaplayici ile gercek trafik uzerinden tahmin yapin.
Her iki model de ayni baglam penceresini sunar: 1M token.
Her iki model de Low cost icin uygundur. Maliyet oncelikliyse DeepSeek: DeepSeek V4 Flash, daha genis baglam gerekiyorsa DeepSeek: DeepSeek V4 Flash secin. Uretim trafigini yonlendirmeden once ikisini de gercek promptlarla test edin.