MultimodalComing soon

DeepSeek V4

Next-generation multimodal MoE model. Launch details and pricing are coming soon.

Overview
Community reports describe V4 as a trillion-parameter MoE model with strong code and math performance and a multimodal roadmap. Official launch timing and pricing are not yet announced.
Best for: Next-gen multimodal use cases, High-complexity reasoning, Early access exploration
  • Reported ~1T parameters with sparse MoE activation.
  • Multimodal roadmap across text, image, and video.
  • Benchmarks and release timing are unconfirmed.
Pricing
Transparent pricing for legacy models. V4 pricing will be announced at launch.
StatusComing soon
Pricing will be announced closer to launch.
Full pricing
Research summary
Compiled from public research notes and internal summaries. Specifications may evolve ahead of official releases.

DeepSeek V4 is positioned as the next-generation multimodal MoE release in the lineup. Public research notes point to trillion-scale capacity with sparse activation, aiming to lift reasoning, code, and long-context reliability without linear compute cost.

Reported goals include longer context windows (often cited at 100K-class), stronger tool-use stability, and higher multimodal fidelity across image and video inputs. Official specifications, benchmarks, and pricing are still pending, so all details should be treated as provisional until launch.

Teams can prepare by validating pipelines against today's models and keeping integrations flexible. Use V3.1 for general workloads, R1 for step-by-step reasoning, Math-7B for cost-sensitive math, Janus-Pro-7B for generation, and VL2 for OCR/document tasks while waiting for V4 access.

Focus areas
The traits to evaluate when choosing this model.
  • Sparse MoE routing at trillion-scale capacity.
  • Long-context expansion and memory efficiency.
  • Multimodal roadmap across image and video.
  • Launch readiness, evaluations, and safety checks.
  • Access policy, pricing, and rollout timing.
Validate benchmarks and latency on your own prompts before committing a production rollout.