Compare/DeepSeek V3.1 Terminus (Reasoning) vs Apertus 70B Instruct

DeepSeek V3.1 Terminus (Reasoning)vsApertus 70B Instruct

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

DeepSeek

DeepSeek V3.1 Terminus (Reasoning)

Input
$1.64/M
Output
$2.75/M
Speed
TTFT
Swiss AI Initiative

Apertus 70B Instruct

Input
$0.82/M
Output
$2.92/M
Speed
TTFT

Winner by Category

Cheaper
Apertus 70B Instruct
Faster (tok/s)
Lower Latency
Benchmarks (2-0)
DeepSeek V3.1 Terminus (Reasoning)

Pricing Comparison

MetricDeepSeek V3.1 Terminus (Reasoning)Apertus 70B Instruct
Input ($/M tokens)$1.64$0.82
Output ($/M tokens)$2.75$2.92
Cost for 1M input + 100K output tokens:
DeepSeek V3.1 Terminus (Reasoning)$1.92
Apertus 70B Instruct$1.11

Speed Comparison

Speed data not available for these models.

Editorial Analysis

Verdict. DeepSeek V3.1 Terminus (Reasoning) wins the overall benchmark matchup 2–0 across 2 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 0.9× the per-million-token cost, DeepSeek V3.1 Terminus (Reasoning) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). DeepSeek V3.1 Terminus (Reasoning) makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. DeepSeek V3.1 Terminus (Reasoning) is strongest on Coding Index (43.5), Intelligence Index (31.4). Apertus 70B Instruct leads on Intelligence Index (2.0).

Speed. Speed data is incomplete for this pair; benchmark and price should decide.

Provider. DeepSeek and Swiss AI Initiative sell to overlapping but distinct developer audiences: DeepSeek tends to ship frontier reasoning models with premium positioning, while Swiss AI Initiative 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 V3.1 Terminus (Reasoning) costs $90.45 ($1085/year); Apertus 70B Instruct costs $68.40 ($821/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): DeepSeek V3.1 Terminus (Reasoning) ≈ $13.70/run, Apertus 70B Instruct ≈ $9.94/run. At agent/realtime scale (200M input / 100M output per million requests): DeepSeek V3.1 Terminus (Reasoning) ≈ $603/run, Apertus 70B Instruct ≈ $456/run. Apertus 70B Instruct 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.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
31.42.0
Coding Index
43.5
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
DeepSeek V3.1 Terminus (Reasoning)2 wins
0 winsApertus 70B Instruct

Frequently Asked Questions

Which is cheaper, DeepSeek V3.1 Terminus (Reasoning) or Apertus 70B Instruct?

Apertus 70B Instruct is cheaper overall. Its blended price (3:1 input/output ratio) is $1.34/M tokens vs $1.92/M for DeepSeek V3.1 Terminus (Reasoning).

Which model performs better on benchmarks?

DeepSeek V3.1 Terminus (Reasoning) wins 2 out of 12 benchmarks compared to 0 for Apertus 70B Instruct. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Both models have comparable generation speeds.

When should I use DeepSeek V3.1 Terminus (Reasoning) vs Apertus 70B Instruct?

Choose based on your priorities: Apertus 70B Instruct for lower cost, DeepSeek V3.1 Terminus (Reasoning) for stronger benchmark performance, and both have comparable speed. For latency-sensitive apps, check the TTFT comparison above.