Compare/GPT-4o mini vs Mistral Small (Sep '24)

GPT-4o minivsMistral Small (Sep '24)

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

OpenAI

GPT-4o mini

Input
$0.15/M
Output
$0.6/M
Speed
101 tok/s
TTFT
1.03s
Mistral

Mistral Small (Sep '24)

Input
$0.2/M
Output
$0.6/M
Speed
143 tok/s
TTFT
0.81s

Winner by Category

Cheaper
GPT-4o mini
Faster (tok/s)
Mistral Small (Sep '24)
Lower Latency
Mistral Small (Sep '24)
Benchmarks (2-0)
GPT-4o mini

Pricing Comparison

MetricGPT-4o miniMistral Small (Sep '24)
Input ($/M tokens)$0.15$0.2
Output ($/M tokens)$0.6$0.6
Cost for 1M input + 100K output tokens:
GPT-4o mini$0.21
Mistral Small (Sep '24)$0.26

Speed Comparison

Output Speed (tokens/s) — higher is better
GPT-4o mini
101 tok/s
Mistral Small (Sep '24)
143 tok/s
Time to First Token (seconds) — lower is better
GPT-4o mini
1.03s
Mistral Small (Sep '24)
0.81s

Editorial Analysis

Verdict. GPT-4o mini 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, Mistral Small (Sep '24) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Mistral Small (Sep '24) makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. GPT-4o mini is strongest on Coding Index (11.4), Intelligence Index (6.7). Mistral Small (Sep '24) leads on Intelligence Index (4.3).

Speed. On throughput, Mistral Small (Sep '24) generates tokens at 143 tok/s versus 101 tok/s — about 29% faster. On time-to-first-token, Mistral Small (Sep '24) responds in 810ms vs 1030ms, which matters most for chat-style UIs.

Provider. OpenAI and Mistral sell to overlapping but distinct developer audiences: OpenAI tends to ship frontier reasoning models with premium positioning, while Mistral 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): GPT-4o mini costs $13.50 ($162/year); Mistral Small (Sep '24) costs $15.00 ($180/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GPT-4o mini ≈ $1.95/run, Mistral Small (Sep '24) ≈ $2.20/run. At agent/realtime scale (200M input / 100M output per million requests): GPT-4o mini ≈ $90/run, Mistral Small (Sep '24) ≈ $100/run. GPT-4o mini 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
6.74.3
Coding Index
11.4
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
GPT-4o mini2 wins
0 winsMistral Small (Sep '24)

Frequently Asked Questions

Which is cheaper, GPT-4o mini or Mistral Small (Sep '24)?

GPT-4o mini is cheaper overall. Its blended price (3:1 input/output ratio) is $0.26/M tokens vs $0.30/M for Mistral Small (Sep '24).

Which model performs better on benchmarks?

GPT-4o mini wins 2 out of 12 benchmarks compared to 0 for Mistral Small (Sep '24). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Mistral Small (Sep '24) generates tokens faster at 143 tok/s vs 101 tok/s. However, Mistral Small (Sep '24) has lower time-to-first-token (0.81s vs 1.03s).

When should I use GPT-4o mini vs Mistral Small (Sep '24)?

Choose based on your priorities: GPT-4o mini for lower cost, GPT-4o mini for stronger benchmark performance, and Mistral Small (Sep '24) for faster generation. For latency-sensitive apps, check the TTFT comparison above.