Head-to-head
DeepSeek-V4 vs Gemini 3.5 Flash: which AI model wins in 2026?
DeepSeek-V4 ($0.87/1M out) and Gemini 3.5 Flash ($9.00/1M out) are two of the most-used AI models in 2026. Across 3 community votes, DeepSeek-V4 leads with 57% approval.
Quick verdict
On Reasoning, pick DeepSeek-V4: the arena rates it 4.5/5 against 3.5/5 for Gemini 3.5 Flash. On budget, DeepSeek-V4 wins: it starts at $0.87/1M out versus $9.00/1M out for Gemini 3.5 Flash.
Line-by-line comparison
Strengths and weaknesses
DeepSeek-V4
- 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
- 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
Gemini 3.5 Flash
- Beats Gemini 3.1 Pro on agentic benchmarks: 76.2% Terminal-Bench 2.1, 1656 Elo GDPval-AA (vs 1314 for 3.1 Pro), 83.6% MCP Atlas
- Artificial Analysis Intelligence Index 50 at high thinking effort, ranking #10 of 170 tracked models
- Very fast generation (~185 output tokens/sec per Artificial Analysis); Google claims 4x faster output than other frontier models
- 1M-token context window (1,048,576) with multimodal input: text, image, audio, video, PDF
- 25% cheaper than Gemini 3.1 Pro ($1.50/$9 vs $2/$12) while outperforming it on production agent workloads
- Adjustable thinking effort (minimal/low/medium/high) plus 50% batch discount and $0.15/1M context caching
- 3x price increase over Gemini 3 Flash ($0.50/$3.00) and 5-6x over 2.5 Flash; HN devs saw it as Google probing price tolerance
- Over-eager and verbose: devs report it ignores completion criteria and embellishes beyond instructions (compared to Claude's 'Sonnet 3.7 moment')
- Reliability complaints on Flash serving: developers report frequent 503 errors during peak periods
- Weaker on long-horizon agentic tasks with arbitrary tool availability, a recurring theme devs report with Google models
- High time-to-first-token (~23s at high thinking effort per Artificial Analysis), poor fit for latency-sensitive chat
Cast your verdict
One recommendation per tool per gladiator. It reshapes the crowd score everyone sees.
The arena’s verdict on DeepSeek-V4
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.
The arena’s verdict on Gemini 3.5 Flash
Pick Gemini 3.5 Flash if you run agentic coding or high-volume multimodal pipelines and want near-Pro quality at 4x the speed: it actually beats Gemini 3.1 Pro on Terminal-Bench and GDPval while costing 25% less. Avoid it if you used the Flash line as a budget tier, since it costs 3x its predecessor Gemini 3 Flash, which remains the cheap option at $0.50/$3.00. Also skip it for latency-sensitive chat at high thinking effort (~23s to first token) or strict, no-embellishment output where its verbosity works against you.
What the crowd says
On DeepSeek-V4
“Tool calling is flaky. Function calls sometimes land as plain text instead of the tool_calls field, and thinking mode 400s on long multi-turn chains. Not agent-ready yet.”
“MIT license on both Pro and Flash weights is the real story. Fine-tune, redistribute, ship commercially, no lawyer needed. Plus 384K output tokens for long-doc generation.”
“MIT weights, 1M context, and output tokens roughly 29x cheaper than Opus 4.8. Cache hits make input basically free. Moved my bulk pipelines over and the bill collapsed.”
On Gemini 3.5 Flash
No verdicts yet. Be the first to speak.
Keep comparing
Frequently asked questions
Is DeepSeek-V4 better than Gemini 3.5 Flash?
The crowd currently sides with DeepSeek-V4: 57% recommend it, versus 50% for Gemini 3.5 Flash (3 votes). On Reasoning, DeepSeek-V4 rates higher (4.5/5 vs 3.5/5). The right pick depends on your use case. The line-by-line comparison on this page breaks down pricing, key specs and arena ratings.
Which is cheaper, DeepSeek-V4 or Gemini 3.5 Flash?
DeepSeek-V4 is cheaper: it starts at $0.87/1M out, while Gemini 3.5 Flash starts at $9.00/1M out.
How much do DeepSeek-V4 and Gemini 3.5 Flash cost per 1M tokens?
DeepSeek-V4: $0.435/1M in (cache hit $0.003625) per 1M input tokens, $0.87/1M out per 1M output tokens. Gemini 3.5 Flash: $1.50/1M in per 1M input tokens, $9.00/1M out per 1M output tokens.