Compare/GPT-3.5 Turbo vs Mistral Large 3

GPT-3.5 TurbovsMistral Large 3

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

OpenAI

GPT-3.5 Turbo

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

Mistral Large 3

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

Winner by Category

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

Pricing Comparison

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

Speed Comparison

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

Editorial Analysis

Verdict. Mistral Large 3 takes the aggregate benchmark matchup 2–0 across 2 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, Mistral Large 3 is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Mistral Large 3 makes more sense when output volume is low and absolute reasoning quality justifies the premium.

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

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

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-3.5 Turbo costs $37.50 ($450/year); Mistral Large 3 costs $37.50 ($450/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GPT-3.5 Turbo ≈ $5.50/run, Mistral Large 3 ≈ $5.50/run. At agent/realtime scale (200M input / 100M output per million requests): GPT-3.5 Turbo ≈ $250/run, Mistral Large 3 ≈ $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
3.215.9
Coding Index
10.720.1
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
GPT-3.5 Turbo0 wins
2 winsMistral Large 3

Frequently Asked Questions

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

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. However, Mistral Large 3 has lower time-to-first-token (1.17s vs —s).

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

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.