Model vs model
Ling 3.1 Flash vs MiniMax M3
Ling 3.1 Flash suits text-based work like terminal tasks, scientific coding and hard reasoning. It scores 43.9 on the Intelligence Index against 29.2 for MiniMax M3, and costs $0.45 per 1M tokens blended against $0.52. Choose MiniMax M3 for long inputs or images and PDFs, since it offers a 512K context window and accepts those formats, while Ling 3.1 Flash has 262K tokens and accepts text only.
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, MiniMax M3 24th. 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 lower bill ($0.45 vs $0.52 per 1M tokens blended)
- you want the higher overall score (43.9 vs 29.2)
- you care about Terminal-Bench 4.0 (terminal tasks): 32.8 vs 2
- you care about SciCode (scientific coding): 56.8 vs 47.1
Pick MiniMax M3 if
- you need a longer context window (512K vs 262K tokens)
- you need to send images and PDFs
How smart is each one?
Of the 10 scores both models have, Ling 3.1 Flash is ahead on 9, and one is within a point.
Every intelligence score we have
Out of 100, higher is better. Ling 3.1 Flash MiniMax M3
Overall
Intelligence Index
43.929.2
By area
Coding
58.6Ling 3.1 Flash: not scored yet
Agentic work
29.5Ling 3.1 Flash: not scored yet
By field of work
Finance & accounting
45.530.1Legal
41.631.5Healthcare & medicine
27.8Ling 3.1 Flash: not scored yet
Economics
49.943.7Engineering
44.331.2Strategy & operations
47.925
Benchmarks
Hard reasoning · Humanity's Last Exam
43.539Science · GPQA Diamond
92.9Ling 3.1 Flash: not scored yet
Scientific coding · SciCode
56.847.1Terminal tasks · Terminal-Bench 4.0
32.82Tool use · τ-Bench Banking
15.3Ling 3.1 Flash: not scored yet
Instruction following · IFBench
82.9Ling 3.1 Flash: not scored yet
Long documents · AA-LCR
82.3 · 83
Our tests
Rule that has to last 4 turns · our test, % of tries passed
33Ling 3.1 Flash: not scored yet
Three bullets, no letter e · our test, % of tries passed
100Ling 3.1 Flash: not scored yet
The specs
| Spec | Ling 3.1 Flash | MiniMax M3 |
|---|---|---|
| Input price | $0.30 per 1M | $0.30 per 1M |
| Output price | $0.90 per 1M | $1.20 per 1M |
| Cost per test task | Not tested | $0.5076 |
| Context window | 262K | 512K |
| Max output | 33K | 512K |
| Accepts | Text | Text, Image, PDF |
| Open weights | Yes | Yes |
| Lab | InclusionAI | MiniMax |
| Released | Sep 2026 | Jun 2026 |
| Knowledge cutoff | Not published | 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 Ling 3.1 Flash or MiniMax M3 cheaper?
Ling 3.1 Flash is cheaper. It charges $0.30 per 1M input tokens and $0.90 per 1M output tokens, against $0.30 and $1.20 for MiniMax M3. Blended 3 parts input to 1 part output, that is $0.45 against $0.52 per 1M tokens.
Which is smarter, Ling 3.1 Flash or MiniMax M3?
Ling 3.1 Flash scores higher on the Artificial Analysis Intelligence Index, 43.9 against 29.2 for MiniMax M3. The biggest differences are on Terminal-Bench 4.0 (32.8 vs 2) and SciCode (56.8 vs 47.1).
Which has the longer context window?
MiniMax M3 accepts 512K tokens, against 262K for Ling 3.1 Flash.
Can I compare Ling 3.1 Flash and MiniMax M3 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.