Key takeaways

• DeepSeek V4 Flash 0731 is a sparse Mixture-of-Experts (MoE) language model with 284B total parameters (13B active at inference), designed for strong reasoning, coding, and tool-use in efficiency-focused deployments.
• The model was re-post-trained to enhance performance in coding, reasoning, and agentic workflows, improving across math, science, and long-context benchmarks while reducing hallucination rates.
• It demonstrates exceptional mathematical problem-solving, achieving 100% accuracy on the AIME 2026 Mathematics Benchmark by consistently providing exact integer answers across diverse advanced topics.
• While strong in Go (70% pass rate) and some Python/JavaScript tasks, the model struggles with Rust (20% pass rate) and certain precise requirements in other languages, often failing on exact error messages or complex library integrations.
• Overall, it achieved a 57.69% pass rate on the DeepSWE benchmark for long-horizon software engineering tasks, highlighting proficiency in core logic but challenges with highly specific constraints and intricate library usage.

Technical specifications

Context length

1M tokens

Max output

—

Architecture

MoE

Modalities

text->text

Parameters

~284B

Open weights

Yes

Licence

MIT

Regions

China

Vendor

DeepSeek

Provider model key

deepseek/deepseek-v4-flash-0731