LANGUAGE MODEL DeepSeek Last updated:

DeepSeek V4 Flash (Reasoning, High Effort)

DeepSeek V4 Flash (Reasoning, High Effort) is an API model from DeepSeek. It’s positioned for general text tasks—work that benefits from iteration, not just one-shot answers.

Intelligence
Good
Speed
Slow
81 tok/s output
Cost
Low
$0.14 in / $0.28 out
Context
1M
Up to 1,000,000 tokens
How are Intelligence, Speed & Cost bucketed?
Intelligence and Speed buckets are percentile ranks on Artificial Analysis. Cost buckets are fixed dollar thresholds keyed off output-token price ($/M out).
Intelligence
  • Top 1%≤ 1%
  • Top 5%≤ 5%
  • Top 10%≤ 10%
  • Good≤ 25%
  • Medium≤ 50%
  • Below avg> 50%
Speed
  • Top 1%≥ 345 tok/s
  • Top 5%≥ 237 tok/s
  • Top 10%≥ 196 tok/s
  • Good≥ 146 tok/s
  • Medium≥ 90 tok/s
  • Slow< 90 tok/s
Cost
  • Freeopen weights · self-host
  • Low< $1 / M out
  • Moderate$1–5 / M out
  • High≥ $5 / M out

Core Capabilities

Long Documents
Handles entire codebases, books, and multi-doc RAG.

Context Window

1M tokens
≈ entire codebase
4k Chat 聊天
32k Long docs 长文档
128k Books 整本书
400k Multi-doc 多文档
1M This model 本模型
10M

Availability

API
Available
Product / App
Not available
Open Source
Not released
Enterprise
Contact sales

Pricing Model

Free / self-host
Open weights — pay only for compute.
Self-host

Capability / Performance

Where this model sits relative to the middle 60% of models in the tree. All scores are 0–10 (higher is better).

Lower 20% Upper 80% This model
Reasoning
AA Intelligence Index · scaled to 10
1.7
5.6
6.4
Coding
SciCode · scaled to 10
1.8
4.3
4.2
Agentic tasks
Terminal-Bench Hard · scaled to 10
0.2
3.6
3.9
Context / memory
Context window size · log-scaled
6.0
9.0
9.0
Cost efficiency
Input price ($/M tokens) · cheaper scores higher
6.2
10.0
10.0
Lower 20% 20th percentile — 20% of models score below this This model Where the current model lands Upper 80% 80th percentile — only 20% of models score above this Percentile boundaries are computed across every model in the tree that reports the underlying benchmark for each capability.

What it feels like

  • Flash tier of V4 — speed-optimised.
  • First open-weights reasoning model that genuinely competes with o1 — broke the closed-source moat
  • ~90% on advanced math benchmarks vs ~83% for GPT-4o; the chain-of-thought is fully visible
  • Trained for ~$5.5M on 2,048 H800s — proof you don't need $100M training runs to reach the frontier

Best use cases

  • Math proofs, logic puzzles, and step-by-step derivations where explicit reasoning helps
  • Coding and engineering tasks that benefit from chain-of-thought
  • On-prem / air-gapped deployments where API models can't go

Tools to try

Not ideal for

  • Casual chat, tone, or creative writing — ChatGPT/Claude feel more polished
  • Multimodal tasks (image / vision) — text-only model

Model Evolution

deepseek-v is DeepSeek's language model family.

View full evolution tree →