Compare/Agnes 2.5 Pro Alpha vs DeepSeek V4 Pro (Reasoning, High Effort)

Agnes 2.5 Pro AlphavsDeepSeek V4 Pro (Reasoning, High Effort)

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

Sapiens AI

Agnes 2.5 Pro Alpha

Input
$0.45/M
Output
$0.9/M
Speed
134 tok/s
TTFT
1.93s
DeepSeek

DeepSeek V4 Pro (Reasoning, High Effort)

Input
$0.435/M
Output
$0.87/M
Speed
70 tok/s
TTFT
0.92s

Winner by Category

Cheaper
DeepSeek V4 Pro (Reasoning, High Effort)
Faster (tok/s)
Agnes 2.5 Pro Alpha
Lower Latency
DeepSeek V4 Pro (Reasoning, High Effort)
Benchmarks (1-6)
DeepSeek V4 Pro (Reasoning, High Effort)

Pricing Comparison

MetricAgnes 2.5 Pro AlphaDeepSeek V4 Pro (Reasoning, High Effort)
Input ($/M tokens)$0.45$0.435
Output ($/M tokens)$0.9$0.87
Cost for 1M input + 100K output tokens:
Agnes 2.5 Pro Alpha$0.54
DeepSeek V4 Pro (Reasoning, High Effort)$0.52

Speed Comparison

Output Speed (tokens/s) — higher is better
Agnes 2.5 Pro Alpha
134 tok/s
DeepSeek V4 Pro (Reasoning, High Effort)
70 tok/s
Time to First Token (seconds) — lower is better
Agnes 2.5 Pro Alpha
1.93s
DeepSeek V4 Pro (Reasoning, High Effort)
0.92s

Editorial Analysis

Verdict. DeepSeek V4 Pro (Reasoning, High Effort) takes the aggregate benchmark matchup 6–1 across 7 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.

Pricing. Both models sit in the budget bracket for output-token pricing. At 1.0× the per-million-token cost, DeepSeek V4 Pro (Reasoning, High Effort) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). DeepSeek V4 Pro (Reasoning, High Effort) makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. Agnes 2.5 Pro Alpha is strongest on GPQA Diamond (88%), Coding Index (58.8), SciCode (42%). DeepSeek V4 Pro (Reasoning, High Effort) leads on GPQA Diamond (91%), IFBench (71%), Coding Index (58.7).

Speed. On throughput, Agnes 2.5 Pro Alpha generates tokens at 134 tok/s versus 70 tok/s — about 47% faster. On time-to-first-token, DeepSeek V4 Pro (Reasoning, High Effort) responds in 922ms vs 1929ms, which matters most for chat-style UIs.

Provider. Sapiens AI and DeepSeek sell to overlapping but distinct developer audiences: Sapiens AI tends to ship frontier reasoning models with premium positioning, while DeepSeek often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.

Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): Agnes 2.5 Pro Alpha costs $27.00 ($324/year); DeepSeek V4 Pro (Reasoning, High Effort) costs $26.10 ($313/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Agnes 2.5 Pro Alpha ≈ $4.05/run, DeepSeek V4 Pro (Reasoning, High Effort) ≈ $3.92/run. At agent/realtime scale (200M input / 100M output per million requests): Agnes 2.5 Pro Alpha ≈ $180/run, DeepSeek V4 Pro (Reasoning, High Effort) ≈ $174/run. DeepSeek V4 Pro (Reasoning, High Effort) becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.

Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.

Head-to-head deltas

  • DeepSeek V4 Pro (Reasoning, High Effort) wins 5 more benchmarks than its opponent — a margin wide enough to call the comparison settled on benchmark terms alone.
  • On throughput, Agnes 2.5 Pro Alpha is 1.90× faster (134 tok/s vs 70 tok/s). For streaming chat or real-time agents this alone often flips the recommendation.
  • Aggregate benchmark score (sum across 12 categories, capped at 100): Agnes 2.5 Pro Alpha = 99, DeepSeek V4 Pro (Reasoning, High Effort) = 105. Within 15% — effectively equivalent if both meet the threshold your product requires.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
38.843.1
Coding Index
58.858.7
Math Index
GPQA Diamond
87.6%90.5%
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
31.9%33.5%
SciCode
42.2%46.4%
IFBench
71.3%
TerminalBench
41.7%
Agnes 2.5 Pro Alpha1 wins
6 winsDeepSeek V4 Pro (Reasoning, High Effort)

Frequently Asked Questions

Which is cheaper, Agnes 2.5 Pro Alpha or DeepSeek V4 Pro (Reasoning, High Effort)?

DeepSeek V4 Pro (Reasoning, High Effort) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.54/M tokens vs $0.56/M for Agnes 2.5 Pro Alpha.

Which model performs better on benchmarks?

DeepSeek V4 Pro (Reasoning, High Effort) wins 6 out of 12 benchmarks compared to 1 for Agnes 2.5 Pro Alpha. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Agnes 2.5 Pro Alpha generates tokens faster at 134 tok/s vs 70 tok/s. However, DeepSeek V4 Pro (Reasoning, High Effort) has lower time-to-first-token (0.92s vs 1.93s).

When should I use Agnes 2.5 Pro Alpha vs DeepSeek V4 Pro (Reasoning, High Effort)?

Choose based on your priorities: DeepSeek V4 Pro (Reasoning, High Effort) for lower cost, DeepSeek V4 Pro (Reasoning, High Effort) for stronger benchmark performance, and Agnes 2.5 Pro Alpha for faster generation. For latency-sensitive apps, check the TTFT comparison above.