Compare/Mistral Large 3 vs GPT-3.5 Turbo

Mistral Large 3vsGPT-3.5 Turbo

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

Mistral

Mistral Large 3

Input
$0.5/M
Output
$1.5/M
Speed
48 tok/s
TTFT
1.17s
OpenAI

GPT-3.5 Turbo

Input
$0.5/M
Output
$1.5/M
Speed
TTFT

Winner by Category

Cheaper
Tie
Faster (tok/s)
Mistral Large 3
Lower Latency
Mistral Large 3
Benchmarks (2-0)
Mistral Large 3

Pricing Comparison

MetricMistral Large 3GPT-3.5 Turbo
Input ($/M tokens)$0.5$0.5
Output ($/M tokens)$1.5$1.5
Cost for 1M input + 100K output tokens:
Mistral Large 3$0.65
GPT-3.5 Turbo$0.65

Speed Comparison

Output Speed (tokens/s) — higher is better
Mistral Large 3
48 tok/s
GPT-3.5 Turbo
Time to First Token (seconds) — lower is better
Mistral Large 3
1.17s
GPT-3.5 Turbo

Editorial Analysis

Verdict. Mistral Large 3 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, GPT-3.5 Turbo is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). GPT-3.5 Turbo makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. Mistral Large 3 is strongest on Coding Index (20.1), Intelligence Index (15.9). GPT-3.5 Turbo leads on Coding Index (10.7), Intelligence Index (3.2).

Speed. Speed data is incomplete for this pair; benchmark and price should decide.

Provider. Mistral and OpenAI sell to overlapping but distinct developer audiences: Mistral tends to ship frontier reasoning models with premium positioning, while OpenAI 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 Large 3 costs $37.50 ($450/year); GPT-3.5 Turbo costs $37.50 ($450/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Mistral Large 3 ≈ $5.50/run, GPT-3.5 Turbo ≈ $5.50/run. At agent/realtime scale (200M input / 100M output per million requests): Mistral Large 3 ≈ $250/run, GPT-3.5 Turbo ≈ $250/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
15.93.2
Coding Index
20.110.7
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Mistral Large 32 wins
0 winsGPT-3.5 Turbo

Frequently Asked Questions

Which is cheaper, Mistral Large 3 or GPT-3.5 Turbo?

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

Which model performs better on benchmarks?

Mistral Large 3 wins 2 out of 12 benchmarks compared to 0 for GPT-3.5 Turbo. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Mistral Large 3 generates tokens faster at 48 tok/s vs — tok/s. Mistral Large 3 also has lower time-to-first-token (1.17s vs —s).

When should I use Mistral Large 3 vs GPT-3.5 Turbo?

Choose based on your priorities: both are similarly priced, Mistral Large 3 for stronger benchmark performance, and Mistral Large 3 for faster generation. For latency-sensitive apps, check the TTFT comparison above.