# DeepSeek-V4: pricing, crowd verdict, pros and cons (2026)

> Open-weights 1.6T MoE with 1M-token context and near-frontier agentic coding at $0.87 per 1M output tokens

Source: [GLAD-AI-TOR](https://glad-ia-tor.com) · Full page: https://glad-ia-tor.com/tool/deepseek-v4
Arena: llm-models · Crowd score: 57% recommend (3 votes, Bayesian-smoothed) · Price: $0.87/1M out

Flagship open-weights MoE family from DeepSeek (V4-Pro 1.6T params/49B active, V4-Flash 284B/13B), released as a preview on April 24, 2026. Brings a 1M-token context window via sparse attention, thinking and non-thinking modes, and MIT-licensed weights on Hugging Face. Positioned as open-source SOTA on agentic coding benchmarks at a fraction of frontier API prices.

## Key facts

- provider: DeepSeek
- contextWindow: 1M tokens (384K max output)
- priceIn: $0.435/1M in (cache hit $0.003625)
- priceOut: $0.87/1M out
- modalities: text only
- openWeights: yes

## Ratings (editorial, 1-5)

- reasoning: 4.5/5
- coding: 4.5/5
- writing: 3.5/5
- speed: 3/5
- valueForMoney: 5/5

## Pros

- 1M-token context window (8x the 128K of V3.2) with up to 384K output tokens, standard on the official API
- Aggressive pricing: $0.435/$0.87 per 1M tokens (V4-Pro), roughly 28.7x cheaper per output token than Claude Opus 4.8; cache-hit input drops to $0.003625/1M (over 99% discount)
- MIT-licensed open weights for both V4-Pro and V4-Flash on Hugging Face: commercial use, fine-tuning and redistribution allowed
- Open-source SOTA on agentic coding: 80.6 on SWE-bench Verified (Think Max config), tied with Gemini 3.1 Pro, plus Codeforces rating 3206 (~rank 23 vs humans)
- Ranks #3 of 93 on the Artificial Analysis Intelligence Index (score 44), well above the 25 average
- Sparse-attention stack cuts 1M-context inference to 27% of V3.2's FLOPs and 10% of its KV cache

## Cons

- Intermittent malformed tool calls: function calls sometimes emitted as plain text in content instead of the tool_calls field (GitHub issue deepseek-ai #1244)
- Thinking mode breaks long multi-turn tool-call chains with 400 errors in agent frameworks (OpenClaw issue #72044, fix still incomplete)
- Developers report it fabricating nonexistent APIs in custom codebases and acting on hallucinated user input in agent loops
- Very verbose (180M eval output tokens vs 95M median) and mid-pack speed at 54.6 tok/s (#39/93), which erodes the low per-token price in practice
- Text only (no vision or audio) and still a preview: the official release planned for mid-July 2026 adds peak-hour pricing that doubles listed API rates during Beijing business hours

## Best for

- agentic coding on a budget
- long-context codebase analysis
- self-hosted and fine-tuned deployments
- high-volume API workloads

## Verdict

Choose DeepSeek-V4 if you want near-frontier reasoning and agentic coding at 3x to nearly 30x below Claude Opus or GPT-5.5 pricing, or if MIT-licensed weights for self-hosting and fine-tuning matter to you. It is a decisive upgrade over V3.2: 8x longer context, far cheaper long-context inference and stronger coding, and the legacy deepseek-chat/reasoner endpoints are deprecated on July 24, 2026 anyway. Avoid it for production agents that depend on rock-solid multi-turn tool calling, where users still report malformed tool calls and fabricated APIs, and for any vision or audio work since it is text only. Latency-sensitive apps should also test first, as its verbosity and mid-pack 54.6 tok/s output speed offset some of the cost advantage, and budget for the peak-hour price doubling arriving with the official mid-July release.

## Pricing note

V4-Pro tier: $0.435/1M in ($0.003625 cache hit), $0.87/1M out; cheaper V4-Flash tier at $0.14/$0.28 ($0.0028 cache hit); the 75% launch discount became permanent pricing on 2026-05-22. The official mid-July 2026 release introduces peak/off-peak pricing, with listed rates doubling during Beijing peak hours.

## Alternatives and head-to-heads

- [Claude Haiku 4.5](https://glad-ia-tor.com/tool/claude-haiku-4-5) (crowd score 67%) · [DeepSeek-V4 vs Claude Haiku 4.5](https://glad-ia-tor.com/vs/deepseek-v4-vs-claude-haiku-4-5)
- [Claude Fable 5](https://glad-ia-tor.com/tool/claude-fable-5) (crowd score 63%) · [DeepSeek-V4 vs Claude Fable 5](https://glad-ia-tor.com/vs/deepseek-v4-vs-claude-fable-5)
- [Claude Opus 4.7](https://glad-ia-tor.com/tool/claude-opus-4-7) (crowd score 57%) · [DeepSeek-V4 vs Claude Opus 4.7](https://glad-ia-tor.com/vs/deepseek-v4-vs-claude-opus-4-7)
- [Claude Sonnet 5](https://glad-ia-tor.com/tool/claude-sonnet-5) (crowd score 57%) · [DeepSeek-V4 vs Claude Sonnet 5](https://glad-ia-tor.com/vs/deepseek-v4-vs-claude-sonnet-5)

Full ranking: https://glad-ia-tor.com/hall-of-fame/llm-models

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