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

DeepSeek V4 Pro (Reasoning, Max Effort)vsAgnes 2.5 Pro Alpha

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

DeepSeek

DeepSeek V4 Pro (Reasoning, Max Effort)

Input
$0.435/M
Output
$0.87/M
Speed
71 tok/s
TTFT
1.02s
Sapiens AI

Agnes 2.5 Pro Alpha

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

Winner by Category

Cheaper
DeepSeek V4 Pro (Reasoning, Max Effort)
Faster (tok/s)
Agnes 2.5 Pro Alpha
Lower Latency
DeepSeek V4 Pro (Reasoning, Max Effort)
Benchmarks (7-0)
DeepSeek V4 Pro (Reasoning, Max Effort)

Pricing Comparison

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

Speed Comparison

Output Speed (tokens/s) — higher is better
DeepSeek V4 Pro (Reasoning, Max Effort)
71 tok/s
Agnes 2.5 Pro Alpha
134 tok/s
Time to First Token (seconds) — lower is better
DeepSeek V4 Pro (Reasoning, Max Effort)
1.02s
Agnes 2.5 Pro Alpha
1.93s

Editorial Analysis

Verdict. DeepSeek V4 Pro (Reasoning, Max Effort) wins the overall benchmark matchup 7–0 across 7 overlapping categories, but raw benchmark score is only one input to the decision.

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

Strengths. DeepSeek V4 Pro (Reasoning, Max Effort) is strongest on GPQA Diamond (89%), IFBench (76%), Coding Index (59.4). Agnes 2.5 Pro Alpha leads on GPQA Diamond (88%), Coding Index (58.8), SciCode (42%).

Speed. On throughput, Agnes 2.5 Pro Alpha generates tokens at 134 tok/s versus 71 tok/s — about 47% faster. On time-to-first-token, DeepSeek V4 Pro (Reasoning, Max Effort) responds in 1021ms vs 1929ms, which matters most for chat-style UIs.

Provider. DeepSeek and Sapiens AI sell to overlapping but distinct developer audiences: DeepSeek tends to ship frontier reasoning models with premium positioning, while Sapiens AI 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): DeepSeek V4 Pro (Reasoning, Max Effort) costs $26.10 ($313/year); Agnes 2.5 Pro Alpha costs $27.00 ($324/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): DeepSeek V4 Pro (Reasoning, Max Effort) ≈ $3.92/run, Agnes 2.5 Pro Alpha ≈ $4.05/run. At agent/realtime scale (200M input / 100M output per million requests): DeepSeek V4 Pro (Reasoning, Max Effort) ≈ $174/run, Agnes 2.5 Pro Alpha ≈ $180/run. DeepSeek V4 Pro (Reasoning, Max Effort) becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.

Recommendation. If you want one safe default, take DeepSeek V4 Pro (Reasoning, Max Effort) — it dominates the benchmark table and the latency profile is 1.9× faster. Agnes 2.5 Pro Alpha only makes sense when you specifically need its pricing tier, an existing contract, or a feature difference that is not measured by the benchmarks above.

Head-to-head deltas

  • DeepSeek V4 Pro (Reasoning, Max Effort) wins 7 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 1.89× faster (134 tok/s vs 71 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): DeepSeek V4 Pro (Reasoning, Max Effort) = 107, Agnes 2.5 Pro Alpha = 99. Within 15% — effectively equivalent if both meet the threshold your product requires.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
44.338.8
Coding Index
59.458.8
Math Index
GPQA Diamond
88.8%87.6%
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
35.9%31.9%
SciCode
50.0%42.2%
IFBench
76.5%
TerminalBench
46.2%
DeepSeek V4 Pro (Reasoning, Max Effort)7 wins
0 winsAgnes 2.5 Pro Alpha

Frequently Asked Questions

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

DeepSeek V4 Pro (Reasoning, Max 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, Max Effort) wins 7 out of 12 benchmarks compared to 0 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 71 tok/s. DeepSeek V4 Pro (Reasoning, Max Effort) also has lower time-to-first-token (1.02s vs 1.93s).

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

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