// head_to_head
GPT-5.4 Mini vs Inkling
Published LiveBench scores across all seven categories, live list pricing, context windows, and the measured cost of a point of capability — for both models, side by side.
Inkling is the better model, at roughly the same price.
Inkling leads by 5.5 points overall and the two list within about 10% of each other, so the cheaper-but-weaker trade-off does not apply. Price parity plus a score gap usually makes this an easy call.
openai
GPT-5.4 Mini
- Blended / 1M
- $1.69
- Context
- 400K
- Released
- Mar 17, 2026
- Overall score
- 66.4
thinkingmachines
Inkling
- Blended / 1M
- $1.72
- Context
- 1.0M
- Released
- Jul 17, 2026
- Overall score
- 71.9
Specs and pricing
| Metric | GPT-5.4 Mini | Inkling |
|---|---|---|
| LiveBench overall Mean of the seven LiveBench category scores, 0–100. Higher is better. | 66.4 | 71.9win |
| Cost per point Measured benchmark spend divided by overall score — dollars per point of capability. | $0.1871 | $0.1766 |
| Blended price / 1M 3:1 input:output mix, the usual shape of production traffic. | $1.69 | $1.72 |
| Input price / 1M | $0.750win | $0.950 |
| Output price / 1M | $4.50 | $4.05win |
| Cached input / 1M Price of an input token served from the prompt cache, where the provider publishes one. | $0.075win | $0.160 |
| Context window | 400K | 1.0Mwin |
| Max output tokens | 128K | 262Kwin |
Benchmarks by category
An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — GPT-5.4 Mini on top, Inkling below, both out of 100.
What each one costs to run
Per-token prices are hard to feel. These are monthly list costs for both models across five workload shapes, using each provider's published cached-input rate where there is one.
| Workload | GPT-5.4 Mini | Inkling |
|---|---|---|
| Support chatbot 1.2K in / 400 out × 200K requests | $491.40/mo | $495.12/mo |
| RAG assistant 8K in / 600 out × 100K requests | $600.00/mo | $687.00/mo |
| Coding agent 40K in / 4K out × 20K requests | $582.00/mo | $641.60/mo |
| Document extraction 20K in / 1.5K out × 50K requests | $1053.75/mo | $1214.25/mo |
| Bulk classification 500 in / 20 out × 5M requests | $1987.50/mo | $2385.00/mo |
Which should you pick?
Quality matters more than the bill
Inkling
Highest overall LiveBench score of the two at 71.9.
The workload is coding or agentic work
Inkling
Leads on agentic coding — 49.4 against 41.7.
You need to fit large documents in one call
Inkling
Wider context window — 1.0M against 400K.
GPT-5.4 Mini vs Inkling FAQ
Which is better, GPT-5.4 Mini or Inkling?
Inkling is the better model, at roughly the same price. Inkling leads by 5.5 points overall and the two list within about 10% of each other, so the cheaper-but-weaker trade-off does not apply. Price parity plus a score gap usually makes this an easy call.
Is GPT-5.4 Mini cheaper than Inkling?
They cost about the same. Both land near $1.69 per million tokens on a 3:1 input:output blend, so price is unlikely to be the deciding factor between them.
GPT-5.4 Mini vs Inkling: which scores higher on benchmarks?
GPT-5.4 Mini scores 66.4 and Inkling scores 71.9 overall on LiveBench, the mean of its seven categories. That is a 5.5-point lead for Inkling. Category scores differ from the overall figure — a model can lead on reasoning and trail on coding, which the per-category table above breaks out.
Which gives better value for money, GPT-5.4 Mini or Inkling?
They are close. GPT-5.4 Mini costs $0.1871 per point of overall capability and Inkling costs $0.1766, a difference small enough that workload shape will matter more than the rate.
Does GPT-5.4 Mini or Inkling have a bigger context window?
Inkling has the larger context window: 400K for GPT-5.4 Mini against 1.0M for Inkling. Note that a window you can fill is not a window you should fill — retrieval quality usually degrades well before the limit, and you pay for every token you put in it.
Do GPT-5.4 Mini and Inkling support prompt caching?
Both publish a cached-input rate: $0.075 per million for GPT-5.4 Mini and $0.160 for Inkling, against full input rates of $0.750 and $0.950. On a workload with a long stable prefix — a system prompt, a tool schema, a retrieved corpus — that changes the economics more than the headline price does.
Related comparisons
How these numbers are produced
- Price — provider list price from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
- Scores — LiveBench release 2026-06-25, using their own category map. Each model shows its strongest published run. A blank means “not evaluated”, never “bad”.
- Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
- “Win” — awarded only past a threshold: one full point on a benchmark score, 10% on a price, 25% on a context window. Anything tighter reports as a tie, because effort settings alone move a LiveBench score by more than that.
Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.