Compare/GPT-5 nano (minimal) vs Jamba 1.5 Mini

GPT-5 nano (minimal)vsJamba 1.5 Mini

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

OpenAI

GPT-5 nano (minimal)

Input
$0.05/M
Output
$0.4/M
Speed
161 tok/s
TTFT
0.86s
AI21 Labs

Jamba 1.5 Mini

Input
$0.2/M
Output
$0.4/M
Speed
TTFT

Winner by Category

Cheaper
GPT-5 nano (minimal)
Faster (tok/s)
GPT-5 nano (minimal)
Lower Latency
GPT-5 nano (minimal)
Benchmarks (1-0)
GPT-5 nano (minimal)

Pricing Comparison

MetricGPT-5 nano (minimal)Jamba 1.5 Mini
Input ($/M tokens)$0.05$0.2
Output ($/M tokens)$0.4$0.4
Cost for 1M input + 100K output tokens:
GPT-5 nano (minimal)$0.09
Jamba 1.5 Mini$0.24

Speed Comparison

Output Speed (tokens/s) — higher is better
GPT-5 nano (minimal)
161 tok/s
Jamba 1.5 Mini
Time to First Token (seconds) — lower is better
GPT-5 nano (minimal)
0.86s
Jamba 1.5 Mini

Editorial Analysis

Verdict. GPT-5 nano (minimal) wins the overall benchmark matchup 1–0 across 1 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, Jamba 1.5 Mini is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Jamba 1.5 Mini makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. GPT-5 nano (minimal) is strongest on Intelligence Index (7.8). Jamba 1.5 Mini leads on Intelligence Index (2.3).

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

Provider. OpenAI and AI21 Labs sell to overlapping but distinct developer audiences: OpenAI tends to ship frontier reasoning models with premium positioning, while AI21 Labs 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-5 nano (minimal) costs $7.50 ($90/year); Jamba 1.5 Mini costs $12.00 ($144/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): GPT-5 nano (minimal) ≈ $1.05/run, Jamba 1.5 Mini ≈ $1.80/run. At agent/realtime scale (200M input / 100M output per million requests): GPT-5 nano (minimal) ≈ $50/run, Jamba 1.5 Mini ≈ $80/run. GPT-5 nano (minimal) 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
7.82.3
Coding Index
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
GPT-5 nano (minimal)1 wins
0 winsJamba 1.5 Mini

Frequently Asked Questions

Which is cheaper, GPT-5 nano (minimal) or Jamba 1.5 Mini?

GPT-5 nano (minimal) is cheaper overall. Its blended price (3:1 input/output ratio) is $0.14/M tokens vs $0.25/M for Jamba 1.5 Mini.

Which model performs better on benchmarks?

GPT-5 nano (minimal) wins 1 out of 12 benchmarks compared to 0 for Jamba 1.5 Mini. See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

GPT-5 nano (minimal) generates tokens faster at 161 tok/s vs — tok/s. GPT-5 nano (minimal) also has lower time-to-first-token (0.86s vs —s).

When should I use GPT-5 nano (minimal) vs Jamba 1.5 Mini?

Choose based on your priorities: GPT-5 nano (minimal) for lower cost, GPT-5 nano (minimal) for stronger benchmark performance, and GPT-5 nano (minimal) for faster generation. For latency-sensitive apps, check the TTFT comparison above.