Pairwise benchmark snapshot · Aug 17, 2026
In this head-to-head showdown, DeepSeek V4 Pro delivers higher overall intelligence and human-preferred responses (Elo 1,536 vs 1,490), while DeepSeek V4 Pro leads in SWE-bench software engineering benchmarks (71.6%), while Gemini 2.0 Flash Thinking is more budget-friendly at $0.4/1M per 1M output tokens. Review the complete breakdown below to determine which model best fits your performance and budget requirements.
9 direct benchmark disciplines evaluated across capability, speed, and cost
Open-weight-adjacent DeepSeek flagship. High reasoning density per dollar.
Google experimental reasoning model that visualizes thoughts in real-time.
Simulate accuracy gains vs added response time & token cost
Reasoning models “think before answering” by generating internal reasoning tokens. Higher effort improves math, coding, and logic accuracy, but increases response delay and token costs.
Simulate accuracy gains vs added response time & token cost
Reasoning models “think before answering” by generating internal reasoning tokens. Higher effort improves math, coding, and logic accuracy, but increases response delay and token costs.
Δ 46 Arena Elo pts
115 tok/s
$0.4 / 1M output
Relative percentile scores computed across all active models in the benchmark catalog.
Comparing top Western standard models with China's leading frontier rival across 6 skill dimensions. Tap any spoke or dot to inspect.
Category wins across reasoning intelligence, generation speed, and token cost.
Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy
Generation throughput and time to first token responsiveness
Cost per million tokens and max context window length
| Benchmark | DeepSeek V4 Pro | Gemini 2.0 Flash Thinking | Advantage Delta |
|---|---|---|---|
| Preference Elo | +46 | ||
| Coding Elo | +29 | ||
| LiveBench | +3.1% | ||
| SWE-bench | +4.8% | ||
| GPQA Diamond | +3% | ||
| Time to first token | +190 ms | ||
| Output speed | 70 tok/s | 115 tok/s | +45 tok/s |
| Input price | $1.32/1M | $0.1/1M | +$1.22/1M |
| Output price | $3.96/1M | $0.4/1M | +$3.56/1M |
| Context window | — |
Simulate monthly production API costs in USD (US Dollar).
Gemini 2.0 Flash Thinking is estimated to save $96.10/month ($1,153/year).
Higher SWE-bench (71.6%).
Lower output list price ($0.4/1M).
Lower TTFT (220 ms).
Larger window (1M).
Gemini 2.0 Flash Thinking is the side marked multimodal in the catalog.
| Target Workload | Recommended Pick | Evaluation Rationale |
|---|---|---|
| Repo / coding agents | DeepSeek V4 Pro | Higher SWE-bench (71.6%). |
| High-volume chat | Gemini 2.0 Flash Thinking | Lower output list price ($0.4/1M). |
| Voice / low-latency UI | Gemini 2.0 Flash Thinking | Lower TTFT (220 ms). |
| Long-document RAG | DeepSeek V4 Pro | Larger window (1M). |
| Screenshots / vision | Gemini 2.0 Flash Thinking | Gemini 2.0 Flash Thinking is the side marked multimodal in the catalog. |
Top DeepSeek vs top Anthropic Elo. Usually V4 Pro vs Opus 5. License and invoice decide as much as Elo.
2026-06 open-weight-adjacent flagship. The usual cheap-vs-Claude question starts here.
Jan 2025 reasoning model. Still searched. V4 Pro is the newer DeepSeek buy.
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