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Reviews and evidence

DeepSeek V4 Flash · Media / benchmark · Customer case

DeepSeek V4 Alters Everything We Knew About Price-Performance Math (Lightning AI)

Lightning AI reports an April 24, 2026 snapshot of about 60+ tokens/s and 79.0% SWE-bench Verified for Flash, with 1M context and persistent tool-loop reasoning as architectural context.

Media / benchmarkCustomer caseEdited 2026-09-20

Test conditions

Test/source conditions
Lightning AI internal use; Pro/Flash and April 24, 2026 pricing are separate
Model version
DeepSeek V4 Flash; do not merge V4 Pro, 0424, 0731, or reasoning tiers unless the source explicitly does so
Collection boundary
Existing source note collected August 17–18, 2026; dynamic facts require refresh

Key data and applicable tasks

Background

DeepSeek released two open-source models, V4-Pro and V4-Flash, which are already running in production environments worldwide (including internally at Lightning AI). An initial assessment from a Lightning AI optimization engineer: "Coding is my primary use case—it's good."

Model positioning

  • DeepSeek-V4-Pro: 1.6T total parameters and 49B active parameters, designed for deep reasoning and agentic coding

  • DeepSeek-V4-Flash: 284B total parameters and 13B active parameters, designed for speed and high-throughput pipelines

  • Both support a 1M-token context window as standard

Improvements over V3.2

DimensionV3.2V4
Context window128K1M (standard)
KV cachebaseline10% of V3.2 (a hybrid compressed sparse attention architecture combining CSA + HCA)
Inference FLOPsbaseline27% of V3.2 (at 1M tokens)
Reasoning between tool callsstateless, restarting each timepersistent, retaining the full chain of thought; a 20-step pipeline does not lose context
SWE-bench Verified~69%Pro 80.6% / Flash 79.0%

Key comparison matrix (prices as of 2026-04-24)

DeepSeek V4-ProDeepSeek V4-FlashDeepSeek V3.2Claude Opus 4.6
Context1M1M128K1M
Input price/1M$1.74 (cache miss) / $0.145 (hit)$0.14 (miss) / $0.028 (hit)$0.28 / $0.028$5.00 / $0.50
Output price/1M$3.48$0.28$0.42$25.00
Open source✅ MIT✅ MIT✅ MIT❌
Speed (approx.)~33 tokens/s60+ tokens/s~35 tokens/sModerate
SWE-bench Verified80.6%79.0%~69%80.8%
LiveCodeBench93.5%91.6%—88.8%
Codeforces32063052—Not reported
Terminal Bench 2.067.9%56.9%—65.4%
GPQA Diamond90.1%88.1%—91.3%

Key takeaways

  • V4-Pro scores 80.6% on SWE-bench Verified, just 0.2 points behind Claude Opus 4.6, while its output price is approximately one-seventh of the latter's ($3.48 vs $25)

  • V4's hybrid compressed attention (CSA/HCA) makes the economics of a 1M-token context practical

  • Persistent reasoning across tool calls is V4's key upgrade for Agent scenarios

  • Pricing and benchmark scores come from the DeepSeek V4 technical report (Max reasoning mode) and Anthropic's pricing page

What this supports

  • Supports comparing the article’s dated price-performance framing with its V3.2/V4 architecture discussion.

What this does not support

  • Does not support treating internal use, old prices, or the Pro/Flash table as current API facts or independent retesting.

Method, limits, and reproduction

The figures, task set, reasoning tier, and client conditions apply only to the listed source and collection snapshot. Different versions, harnesses, or providers must not be compared directly; undisclosed parameters remain unknown.

For a reproduction, fix the model version, provider or client, reasoning tier, tools, task-set version, sample count, and collection date, and record failures, retries, and human corrections. Full steps are in the source notes below.

Original source

Lightning AI blog · Frances Fedoriska · Original publication date 2026-04-27 · Site edit date 2026-09-20

Open original source

DeepSeek V4 Flash

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Pricing · English

DeepSeek V4 Flash Pricing: What You Pay in 2026

DeepSeek V4 Flash pricing changed with the V4.1 migration. See the current cache, peak-hour, output, and workload cost math before you budget.

Related reviews

DeepSeek V4 Flash 0731 Benchmarks, Pricing & Speed (BenchLM)BenchLM’s 0731 snapshot lists a 1M context window, Agentic 51.9, Coding 48.5, and Knowledge 61.1, with many scores attributed back to the official report.DeepSeek V4 Flash Third-Party Aggregator Data (Command Code / flaq.ai / OpenRouter / BenchLM Supplement)Command Code, flaq, OpenRouter, and BenchLM aggregate model IDs, prices, and capability fields whose collection windows may differ.The Official DeepSeek V4-Flash Is Here! AI Developers Test It: "Fantastic" Pricing, Agent Capabilities Close to Top-Tier ModelsEastmoney relays developer cases: Hermes + Flash took about 40 seconds versus GPT + Codex at about 1:47, and another task used about 510K tokens and CNY 0.53.DeepSeek V4 Flash at $0.112/M Output After the Price Increase (Reddit r/DeepSeek)After the increase, a Reddit post relays InferX’s third-party quote of $0.056/M input and about $0.112/M output; this is a provider offer, not a controlled measurement.Configure reasoning tiers and continue tool callsTurn low/high/max, tool results, and reasoning_content handoff into a checkable integration path.Connect DeepSeek to Codex with the official configurationBack up local configuration, use the official script or minimal provider fields, and verify with a reversible task.Delegate in layers and synthesize a monograph with DSHThe source publishes a complete starting prompt with research, pushback, editing, and final synthesis targeting one cited Markdown artifact.Structure DeepSeek tasks with the CRISPE frameworkTurn role, request, context, constraints, style, and experiments into an explicit task contract.