Model vs model
Ling 3.1 Flash vs Llama 4 Maverick
Pick Ling 3.1 Flash for most reasoning and coding work, since it scores 43.9 on the Intelligence Index against 9.3 for Llama 4 Maverick and leads on every shared benchmark. Its cost is $0.45 per 1M tokens blended, against $0.42 for Llama 4 Maverick. Choose Llama 4 Maverick when price is the deciding factor, or when you need image input, which Ling 3.1 Flash lacks.
At a glance
Longer bar means the bigger number.
Blended price · per 1M tokens, lower is better
Intelligence Index · Artificial Analysis, higher is better
Context window · tokens it can read at once
Where they sit among all 44 models
Ling 3.1 Flash ranks 12th of the 43 models with an Intelligence Index, Llama 4 Maverick 42nd. 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 Ling 3.1 Flash.
Which one to pick
Pick Ling 3.1 Flash if
- you want the higher overall score (43.9 vs 9.3)
- you care about Humanity's Last Exam (hard reasoning): 43.5 vs 4.9
- you care about Terminal-Bench 4.0 (terminal tasks): 32.8 vs 0
- you need a longer context window (262K vs 128K tokens)
Pick Llama 4 Maverick if
- you want the lower bill ($0.42 vs $0.45 per 1M tokens blended)
- you need to send images
How smart is each one?
Of the 10 scores both models have, Ling 3.1 Flash is ahead on every one.
Every intelligence score we have
Out of 100, higher is better. Ling 3.1 Flash Llama 4 Maverick
Overall
Intelligence Index
43.99.3
By area
Coding
16.3Ling 3.1 Flash: not scored yet
Math
19.3Ling 3.1 Flash: not scored yet
Agentic work
0.6Ling 3.1 Flash: not scored yet
By field of work
Finance & accounting
45.59Legal
41.611.5Economics
49.913Engineering
44.311.3Strategy & operations
47.97.6
Benchmarks
Hard reasoning · Humanity's Last Exam
43.54.9Science · GPQA Diamond
67.1Ling 3.1 Flash: not scored yet
Knowledge · MMLU-Pro
80.9Ling 3.1 Flash: not scored yet
Competitive coding · LiveCodeBench
39.7Ling 3.1 Flash: not scored yet
Scientific coding · SciCode
56.831.7Terminal tasks · Terminal-Bench 4.0
32.80Tool use · τ-Bench Banking
3.7Ling 3.1 Flash: not scored yet
Instruction following · IFBench
43Ling 3.1 Flash: not scored yet
Long documents · AA-LCR
82.350Competition math · AIME 2025
19.3Ling 3.1 Flash: not scored yet
Competition math · AIME 2024
39Ling 3.1 Flash: not scored yet
Math · MATH-500
88.9Ling 3.1 Flash: not scored yet
The specs
| Spec | Ling 3.1 Flash | Llama 4 Maverick |
|---|---|---|
| Input price | $0.30 per 1M | $0.24 per 1M |
| Output price | $0.90 per 1M | $0.97 per 1M |
| Cost per test task | Not tested | Not tested |
| Context window | 262K | 128K |
| Max output | 33K | 8K |
| Accepts | Text | Text, Image |
| Open weights | Yes | Yes |
| Lab | InclusionAI | Meta |
| Released | Sep 2026 | Apr 2025 |
| Knowledge cutoff | Not published | Aug 2024 |
Blended price weighs 3 parts input to 1 part output. List prices from models.dev.
Questions
Is Ling 3.1 Flash or Llama 4 Maverick cheaper?
Llama 4 Maverick is cheaper. It charges $0.24 per 1M input tokens and $0.97 per 1M output tokens, against $0.30 and $0.90 for Ling 3.1 Flash. Blended 3 parts input to 1 part output, that is $0.42 against $0.45 per 1M tokens.
Which is smarter, Ling 3.1 Flash or Llama 4 Maverick?
Ling 3.1 Flash scores higher on the Artificial Analysis Intelligence Index, 43.9 against 9.3 for Llama 4 Maverick. The biggest differences are on Humanity's Last Exam (43.5 vs 4.9) and Terminal-Bench 4.0 (32.8 vs 0).
Which has the longer context window?
Ling 3.1 Flash accepts 262K tokens, against 128K for Llama 4 Maverick.
Can I compare Ling 3.1 Flash and Llama 4 Maverick 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 SimpleQA, which is from Epoch AI, and the Uncensored score, which is from the UGI Leaderboard. 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 October 25, 2026.