Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Trinity Large Thinking | DeepSeek V3 (Dec '24) |
|---|---|---|
| Input ($/M tokens) | $0.25 | $0.36 |
| Output ($/M tokens) | $0.9 | $0.89 |
Verdict. Trinity Large Thinking 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 1.0× the per-million-token cost, DeepSeek V3 (Dec '24) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). DeepSeek V3 (Dec '24) makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Trinity Large Thinking is strongest on Coding Index (25.8), Intelligence Index (18.7). DeepSeek V3 (Dec '24) leads on Coding Index (23.0), Intelligence Index (14.2).
Speed. Speed data is incomplete for this pair; benchmark and price should decide.
Provider. Arcee AI and DeepSeek sell to overlapping but distinct developer audiences: Arcee 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): Trinity Large Thinking costs $21.00 ($252/year); DeepSeek V3 (Dec '24) costs $24.15 ($290/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Trinity Large Thinking ≈ $3.05/run, DeepSeek V3 (Dec '24) ≈ $3.58/run. At agent/realtime scale (200M input / 100M output per million requests): Trinity Large Thinking ≈ $140/run, DeepSeek V3 (Dec '24) ≈ $161/run. Trinity Large Thinking 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.
Data from Artificial Analysis API — 12 benchmarks
Trinity Large Thinking is cheaper overall. Its blended price (3:1 input/output ratio) is $0.41/M tokens vs $0.49/M for DeepSeek V3 (Dec '24).
Trinity Large Thinking wins 2 out of 12 benchmarks compared to 0 for DeepSeek V3 (Dec '24). See the detailed benchmark chart above for per-category results.
Trinity Large Thinking generates tokens faster at 314 tok/s vs — tok/s. Trinity Large Thinking also has lower time-to-first-token (1.15s vs —s).
Choose based on your priorities: Trinity Large Thinking for lower cost, Trinity Large Thinking for stronger benchmark performance, and Trinity Large Thinking for faster generation. For latency-sensitive apps, check the TTFT comparison above.