Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Ling 2.6 Flash | Step 3.5 Flash 2603 |
|---|---|---|
| Input ($/M tokens) | $0.1 | $0.1 |
| Output ($/M tokens) | $0.3 | $0.3 |
Verdict. Step 3.5 Flash 2603 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, Step 3.5 Flash 2603 is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Step 3.5 Flash 2603 makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Ling 2.6 Flash is strongest on GPQA Diamond (59%), IFBench (57%), SciCode (27%). Step 3.5 Flash 2603 leads on GPQA Diamond (83%), IFBench (67%), SciCode (39%).
Speed. On throughput, Step 3.5 Flash 2603 generates tokens at 297 tok/s versus 156 tok/s — about 48% faster. On time-to-first-token, Ling 2.6 Flash responds in 667ms vs 752ms, which matters most for chat-style UIs.
Provider. InclusionAI and StepFun sell to overlapping but distinct developer audiences: InclusionAI tends to ship frontier reasoning models with premium positioning, while StepFun 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): Ling 2.6 Flash costs $7.50 ($90/year); Step 3.5 Flash 2603 costs $7.50 ($90/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Ling 2.6 Flash ≈ $1.10/run, Step 3.5 Flash 2603 ≈ $1.10/run. At agent/realtime scale (200M input / 100M output per million requests): Ling 2.6 Flash ≈ $50/run, Step 3.5 Flash 2603 ≈ $50/run.
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
Data from Artificial Analysis API — 12 benchmarks
Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.
Step 3.5 Flash 2603 wins 6 out of 12 benchmarks compared to 1 for Ling 2.6 Flash. See the detailed benchmark chart above for per-category results.
Step 3.5 Flash 2603 generates tokens faster at 297 tok/s vs 156 tok/s. Ling 2.6 Flash also has lower time-to-first-token (0.67s vs 0.75s).
Choose based on your priorities: both are similarly priced, Step 3.5 Flash 2603 for stronger benchmark performance, and Step 3.5 Flash 2603 for faster generation. For latency-sensitive apps, check the TTFT comparison above.