Compare/Mistral Small 3 vs Step 3.5 Flash 2603

Mistral Small 3vsStep 3.5 Flash 2603

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

Mistral

Mistral Small 3

Input
$0.1/M
Output
$0.3/M
Speed
142 tok/s
TTFT
0.80s
StepFun

Step 3.5 Flash 2603

Input
$0.1/M
Output
$0.3/M
Speed
214 tok/s
TTFT
1.14s

Winner by Category

Cheaper
Tie
Faster (tok/s)
Step 3.5 Flash 2603
Lower Latency
Mistral Small 3
Benchmarks (0-1)
Step 3.5 Flash 2603

Pricing Comparison

MetricMistral Small 3Step 3.5 Flash 2603
Input ($/M tokens)$0.1$0.1
Output ($/M tokens)$0.3$0.3
Cost for 1M input + 100K output tokens:
Mistral Small 3$0.13
Step 3.5 Flash 2603$0.13

Speed Comparison

Output Speed (tokens/s) — higher is better
Mistral Small 3
142 tok/s
Step 3.5 Flash 2603
214 tok/s
Time to First Token (seconds) — lower is better
Mistral Small 3
0.80s
Step 3.5 Flash 2603
1.14s

Editorial Analysis

Verdict. Step 3.5 Flash 2603 takes the aggregate benchmark matchup 1–0 across 1 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. Mistral Small 3 is strongest on Intelligence Index (6.7). Step 3.5 Flash 2603 leads on Intelligence Index (26.5).

Speed. On throughput, Step 3.5 Flash 2603 generates tokens at 214 tok/s versus 142 tok/s — about 33% faster. On time-to-first-token, Mistral Small 3 responds in 800ms vs 1140ms, which matters most for chat-style UIs.

Provider. Mistral and StepFun sell to overlapping but distinct developer audiences: Mistral 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): Mistral Small 3 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): Mistral Small 3 ≈ $1.10/run, Step 3.5 Flash 2603 ≈ $1.10/run. At agent/realtime scale (200M input / 100M output per million requests): Mistral Small 3 ≈ $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

  • On throughput, Step 3.5 Flash 2603 is 1.50× faster (214 tok/s vs 142 tok/s). For streaming chat or real-time agents this alone often flips the recommendation.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
6.726.5
Coding Index
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Mistral Small 30 wins
1 winsStep 3.5 Flash 2603

Frequently Asked Questions

Which is cheaper, Mistral Small 3 or Step 3.5 Flash 2603?

Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.

Which model performs better on benchmarks?

Step 3.5 Flash 2603 wins 1 out of 12 benchmarks compared to 0 for Mistral Small 3. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Step 3.5 Flash 2603 generates tokens faster at 214 tok/s vs 142 tok/s. Mistral Small 3 also has lower time-to-first-token (0.80s vs 1.14s).

When should I use Mistral Small 3 vs Step 3.5 Flash 2603?

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.