Compare/Jamba 1.7 Large vs Mistral Medium

Jamba 1.7 LargevsMistral Medium

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

AI21 Labs

Jamba 1.7 Large

Input
$2/M
Output
$8/M
Speed
54 tok/s
TTFT
0.86s
Mistral

Mistral Medium

Input
$2.75/M
Output
$8.1/M
Speed
73 tok/s
TTFT
0.40s

Winner by Category

Cheaper
Jamba 1.7 Large
Faster (tok/s)
Mistral Medium
Lower Latency
Mistral Medium
Benchmarks (12-0)
Jamba 1.7 Large

Pricing Comparison

MetricJamba 1.7 LargeMistral Medium
Input ($/M tokens)$2$2.75
Output ($/M tokens)$8$8.1
Cost for 1M input + 100K output tokens:
Jamba 1.7 Large$2.80
Mistral Medium$3.56

Speed Comparison

Output Speed (tokens/s) — higher is better
Jamba 1.7 Large
54 tok/s
Mistral Medium
73 tok/s
Time to First Token (seconds) — lower is better
Jamba 1.7 Large
0.86s
Mistral Medium
0.40s

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
10.99.0
Coding Index
7.8
Math Index
2.3
GPQA Diamond
39.0%34.9%
MMLU-Pro
57.7%49.1%
LiveCodeBench
18.1%9.9%
AIME 2025
2.3%
MATH-500
60.0%40.5%
Humanity's Last Exam
3.8%3.4%
SciCode
18.8%11.8%
IFBench
35.2%
TerminalBench
2.3%
Jamba 1.7 Large12 wins
0 winsMistral Medium

Frequently Asked Questions

Which is cheaper, Jamba 1.7 Large or Mistral Medium?

Jamba 1.7 Large is cheaper overall. Its blended price (3:1 input/output ratio) is $3.50/M tokens vs $4.09/M for Mistral Medium.

Which model performs better on benchmarks?

Jamba 1.7 Large wins 12 out of 12 benchmarks compared to 0 for Mistral Medium. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

Mistral Medium generates tokens faster at 73 tok/s vs 54 tok/s. However, Mistral Medium has lower time-to-first-token (0.40s vs 0.86s).

When should I use Jamba 1.7 Large vs Mistral Medium?

Choose based on your priorities: Jamba 1.7 Large for lower cost, Jamba 1.7 Large for stronger benchmark performance, and Mistral Medium for faster generation. For latency-sensitive apps, check the TTFT comparison above.