Compare/gpt-oss-120b (high) vs Mistral Small (Feb '24)

gpt-oss-120b (high)vsMistral Small (Feb '24)

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

OpenAI

gpt-oss-120b (high)

Input
$0.15/M
Output
$0.6/M
Speed
161 tok/s
TTFT
0.88s
Mistral

Mistral Small (Feb '24)

Input
$0.15/M
Output
$0.6/M
Speed
150 tok/s
TTFT
0.78s

Winner by Category

Cheaper
Tie
Faster (tok/s)
gpt-oss-120b (high)
Lower Latency
Mistral Small (Feb '24)
Benchmarks (2-0)
gpt-oss-120b (high)

Pricing Comparison

Metricgpt-oss-120b (high)Mistral Small (Feb '24)
Input ($/M tokens)$0.15$0.15
Output ($/M tokens)$0.6$0.6
Cost for 1M input + 100K output tokens:
gpt-oss-120b (high)$0.21
Mistral Small (Feb '24)$0.21

Speed Comparison

Output Speed (tokens/s) — higher is better
gpt-oss-120b (high)
161 tok/s
Mistral Small (Feb '24)
150 tok/s
Time to First Token (seconds) — lower is better
gpt-oss-120b (high)
0.88s
Mistral Small (Feb '24)
0.78s

Editorial Analysis

Verdict. gpt-oss-120b (high) 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 (Feb '24) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Mistral Small (Feb '24) makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. gpt-oss-120b (high) is strongest on Coding Index (30.4), Intelligence Index (24.1). Mistral Small (Feb '24) leads on Intelligence Index (3.2).

Speed. Throughput is comparable — 161 tok/s vs 150 tok/s — so generation speed shouldn't drive your choice here. Look at the per-benchmark wins instead.

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-oss-120b (high) costs $13.50 ($162/year); Mistral Small (Feb '24) costs $13.50 ($162/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): gpt-oss-120b (high) ≈ $1.95/run, Mistral Small (Feb '24) ≈ $1.95/run. At agent/realtime scale (200M input / 100M output per million requests): gpt-oss-120b (high) ≈ $90/run, Mistral Small (Feb '24) ≈ $90/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.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
24.13.2
Coding Index
30.4
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
gpt-oss-120b (high)2 wins
0 winsMistral Small (Feb '24)

Frequently Asked Questions

Which is cheaper, gpt-oss-120b (high) or Mistral Small (Feb '24)?

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

Which model performs better on benchmarks?

gpt-oss-120b (high) wins 2 out of 12 benchmarks compared to 0 for Mistral Small (Feb '24). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

gpt-oss-120b (high) generates tokens faster at 161 tok/s vs 150 tok/s. However, Mistral Small (Feb '24) has lower time-to-first-token (0.78s vs 0.88s).

When should I use gpt-oss-120b (high) vs Mistral Small (Feb '24)?

Choose based on your priorities: both are similarly priced, gpt-oss-120b (high) for stronger benchmark performance, and gpt-oss-120b (high) for faster generation. For latency-sensitive apps, check the TTFT comparison above.