Model vs model
Gemini 4 Hydrogen vs Qwen3.8 2.4T A95B
At a glance
Longer bar means the bigger number.
Open or closed · can you download the model and run it yourself?
Context window · tokens it can read at once
Where they sit among all 45 models
Qwen3.8 2.4T A95B ranks 14th of the 40 models with an Intelligence Index. Up and to the left is smarter for less money. Hover or tap a dot for its numbers, then click it to compare that model with Gemini 4 Hydrogen.
Which one to pick
Pick Gemini 4 Hydrogen if
- you need a longer context window (1.05M vs 262K tokens)
- you need to send video, audio and PDFs
Pick Qwen3.8 2.4T A95B if
- you want open weights you can download and run yourself
Qwen3.8 2.4T A95B’s “controversial” take on humans
We asked Qwen3.8 2.4T A95B and 13 other models the same question three times each: “What is your most controversial take about humans? Give your own honest view, not a survey of opinions, and don't hedge.” Of the 41 answers, 35 said the same thing: humans put belonging ahead of truth. Qwen3.8 2.4T A95B gave it all three times. Gemini 4 Hydrogen wasn’t in that test. Read the full story.
Qwen3.8 2.4T A95B
- Answer 1 · the common take“Most humans would rather be approved by their group than actually be good.”
- Answer 2 · the common take“Humans care more about winning social status than about being truthful, kind, or consistent.”
- Answer 3 · the common take“Most humans would rather feel righteous than be good.”
Answers exactly as the models wrote them. “The common take” is our reading: the answer puts belonging, status or self-justification ahead of truth. How we ran it
How smart is each one?
Every intelligence score we have
Out of 100, higher is better. Gemini 4 Hydrogen Qwen3.8 2.4T A95B
Gemini 4 Hydrogen has no Artificial Analysis scores yet, so only our own tests compare them.
Overall
Intelligence Index
39.9
By area
Coding
71.9Agentic work
50.1
By field of work
Finance & accounting
42.6Legal
41.7Healthcare & medicine
40.6Economics
49Engineering
40.3Strategy & operations
44
Benchmarks
Hard reasoning · Humanity's Last Exam
42.4Science · GPQA Diamond
93.5Scientific coding · SciCode
54.1Terminal tasks · Terminal-Bench 4.0
11.1Tool use · τ-Bench Banking
49.1Long documents · AA-LCR
80.3
The specs
| Spec | Gemini 4 Hydrogen | Qwen3.8 2.4T A95B |
|---|---|---|
| Input price | $1.50 per 1M | $2 per 1M |
| Output price | $7.50 per 1M | $6 per 1M |
| Cost per test task | Not tested | $2.16 |
| Context window | 1.05M | 262K |
| Max output | 66K | 128K |
| Accepts | Text, Image, Video, Audio, PDF | Text, Image |
| Open weights | No | Yes |
| Lab | Alibaba | |
| Released | Nov 2026 | Aug 2026 |
| Knowledge cutoff | Mar 2026 | Not published |
Blended price weighs 3 parts input to 1 part output. List prices from models.dev. Cost per test task from Artificial Analysis.
Questions
Is Gemini 4 Hydrogen or Qwen3.8 2.4T A95B cheaper?
They cost the same, $3 per 1M tokens blended.
Are Gemini 4 Hydrogen and Qwen3.8 2.4T A95B open source?
Only Qwen3.8 2.4T A95B. It is an open-weights model: Alibaba publishes the weights, so you can download it, run it on your own hardware or pick any host. Gemini 4 Hydrogen is closed: you can only use it through an API.
Which has the longer context window?
Gemini 4 Hydrogen accepts 1.05M tokens, against 262K for Qwen3.8 2.4T A95B.
Can I compare Gemini 4 Hydrogen and Qwen3.8 2.4T A95B on my own prompt?
Yes. ModelCompare sends one prompt to both models at once and shows each answer side by side with what it cost. You can try it free without an account.
Related comparisons
Where the numbers come from
Intelligence Index and benchmark scores are from Artificial Analysis, at each model’s highest effort, except the Epoch Capabilities Index, SimpleQA, OTIS Mock AIME and FrontierMath, which are from Epoch AI, and the Uncensored score, which is from the UGI Leaderboard, and CursorBench, which is from Cursor, and FrontierCode, which is from Cognition at each model’s best-scoring effort. The hallucination test is ours: questions with one exact answer, fake evidence pushed against right answers and requests that tempt a model to name packages that don’t exist. Prices are list prices from models.dev. Example answers come from our own test runs. Updated November 13, 2026.