Compare/Mistral Large (Feb '24) vs GPT-5.6 Terra (high)

Mistral Large (Feb '24)vsGPT-5.6 Terra (high)

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

Mistral

Mistral Large (Feb '24)

Input
$4/M
Output
$12/M
Speed
TTFT
OpenAI

GPT-5.6 Terra (high)

Input
$2/M
Output
$12/M
Speed
103 tok/s
TTFT
2.33s

Winner by Category

Cheaper
GPT-5.6 Terra (high)
Faster (tok/s)
GPT-5.6 Terra (high)
Lower Latency
GPT-5.6 Terra (high)
Benchmarks (0-2)
GPT-5.6 Terra (high)

Pricing Comparison

MetricMistral Large (Feb '24)GPT-5.6 Terra (high)
Input ($/M tokens)$4$2
Output ($/M tokens)$12$12
Cost for 1M input + 100K output tokens:
Mistral Large (Feb '24)$5.20
GPT-5.6 Terra (high)$3.20

Speed Comparison

Output Speed (tokens/s) — higher is better
Mistral Large (Feb '24)
GPT-5.6 Terra (high)
103 tok/s
Time to First Token (seconds) — lower is better
Mistral Large (Feb '24)
GPT-5.6 Terra (high)
2.33s

Editorial Analysis

Verdict. GPT-5.6 Terra (high) 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 mid-tier bracket for output-token pricing. At 1.0× the per-million-token cost, GPT-5.6 Terra (high) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). GPT-5.6 Terra (high) makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. Mistral Large (Feb '24) is strongest on Intelligence Index (4.1). GPT-5.6 Terra (high) leads on Coding Index (67.1), Intelligence Index (50.1).

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 (Feb '24) costs $300.00 ($3600/year); GPT-5.6 Terra (high) costs $240.00 ($2880/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Mistral Large (Feb '24) ≈ $44.00/run, GPT-5.6 Terra (high) ≈ $34.00/run. At agent/realtime scale (200M input / 100M output per million requests): Mistral Large (Feb '24) ≈ $2000/run, GPT-5.6 Terra (high) ≈ $1600/run. GPT-5.6 Terra (high) 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
4.150.1
Coding Index
67.1
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Mistral Large (Feb '24)0 wins
2 winsGPT-5.6 Terra (high)

Frequently Asked Questions

Which is cheaper, Mistral Large (Feb '24) or GPT-5.6 Terra (high)?

GPT-5.6 Terra (high) is cheaper overall. Its blended price (3:1 input/output ratio) is $4.50/M tokens vs $6.00/M for Mistral Large (Feb '24).

Which model performs better on benchmarks?

GPT-5.6 Terra (high) wins 2 out of 12 benchmarks compared to 0 for Mistral Large (Feb '24). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

GPT-5.6 Terra (high) generates tokens faster at 103 tok/s vs — tok/s. However, GPT-5.6 Terra (high) has lower time-to-first-token (2.33s vs —s).

When should I use Mistral Large (Feb '24) vs GPT-5.6 Terra (high)?

Choose based on your priorities: GPT-5.6 Terra (high) for lower cost, GPT-5.6 Terra (high) for stronger benchmark performance, and GPT-5.6 Terra (high) for faster generation. For latency-sensitive apps, check the TTFT comparison above.