AI model comparison
MiniMax M2.7 vs Qwen3.5-35B-A3B
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
MiniMax
MiniMax M2.7
MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement.
- Input / 1M
- $0.21
- Output / 1M
- $0.84
- Context
- 205K
Qwen
Qwen3.5-35B-A3B
The Qwen3.5 Series 35B-A3B is a native vision-language model designed with a hybrid architecture that integrates linear attention mechanisms and a sparse mixture-of-experts model, achieving higher inference efficiency.
- Input / 1M
- $0.08
- Output / 1M
- $0.75
- Context
- 262K
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Qwen3.5-35B-A3B
1.6x cheaper for a typical chat
Higher intelligence score
MiniMax M2.7
22.8 vs 19.3 on Artificial Analysis
Larger context window
Qwen3.5-35B-A3B
262K vs 205K tokens
Newer release
MiniMax M2.7
Released March 18, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Qwen3.5-35B-A3B19.3Coding index
Qwen3.5-35B-A3BNot availableAgentic index
Qwen3.5-35B-A3BNot availablePricing
MiniMax M2.7 vs Qwen3.5-35B-A3B API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | Qwen3.5-35B-A3B | |
|---|---|---|
| Input tokensPer 1M tokens | $0.21 | $0.08 |
| Output tokensPer 1M tokens | $0.84 | $0.75 |
| Cached input (read)Per 1M tokens | $0.04 | $0.04 |
| Cache writePer 1M tokens | Not available | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Qwen3.5-35B-A3B$0.54Coding task
30K in, 4K out
Qwen3.5-35B-A3B$5.40$4.20 cachedLong document summary
150K in, 2K out
Qwen3.5-35B-A3B$13.50$7.50 cachedSpecs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | Qwen3.5-35B-A3B | |
|---|---|---|
| Context window | 205K tokens | 262K tokens |
| Max output | 177K tokens | 33K tokens |
| Input types | Text | Image, Text, Video |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | March 18, 2026 | February 25, 2026 |
Features
Supported features
API features available for each model.
| Metric | Qwen3.5-35B-A3B | |
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Not supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Not supported |
Keep exploring
More on these models
Other head-to-heads, the full model page, and the alternatives list for each model.
- MiniMax M2.7 vs DeepSeek V4 Flash 0423
- MiniMax M2.7 vs Hy3
- MiniMax M2.7 vs MiniMax M3
- MiniMax M2.7 vs Solar Mini 4
- MiniMax M2.7 vs MiMo-V2.5-Pro
- MiniMax M2.7 vs DeepSeek V3.2
- MiniMax M2.7 vs Qwen3.7 Plus
- MiniMax M2.7 vs Gemini 3.5 Flash Lite
- MiniMax M2.7 vs MiniMax M2.5
- MiniMax M2.7 vs Ling 3.0 Flash Fin
- MiniMax M2.7 vs MiniMax M2.1
- MiniMax M2.7 vs GPT-5.4 Nano
- MiniMax M2.7 vs MiniMax M2
Qwen3.5-35B-A3BView full model details- Qwen3.5-35B-A3B vs DeepSeek V4 Flash 0423
- Qwen3.5-35B-A3B vs DeepSeek V3.2
- Qwen3.5-35B-A3B vs GPT-5.4 Nano
- Qwen3.5-35B-A3B vs Step 3.7 Flash
- Qwen3.5-35B-A3B vs LongCat 2.0
- Qwen3.5-35B-A3B vs MiniMax M2
- Qwen3.5-35B-A3B vs Qwen3.6 35B A3B
- Qwen3.5-35B-A3B vs Qwen3.5-122B-A10B
- Qwen3.5-35B-A3B vs Muse Glimmer 30B
Our take
Qwen3.5-35B-A3B is 1.6x cheaper for a typical chat. MiniMax M2.7 scores higher on the Artificial Analysis Intelligence Index (22.8 vs 19.3). Qwen3.5-35B-A3B has the larger context window (262K vs 205K tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is MiniMax M2.7 or Qwen3.5-35B-A3B cheaper?
Qwen3.5-35B-A3B is cheaper for a typical chat (2K input tokens and 500 output tokens). Qwen3.5-35B-A3B costs $0.08 per 1M input tokens and $0.75 per 1M output tokens, while MiniMax M2.7 costs $0.21 per 1M input tokens and $0.84 per 1M output tokens.
Which has a bigger context window, MiniMax M2.7 or Qwen3.5-35B-A3B?
Qwen3.5-35B-A3B supports up to 262K tokens of context, compared with 205K for MiniMax M2.7.
Is MiniMax M2.7 smarter than Qwen3.5-35B-A3B?
On the Artificial Analysis Intelligence Index, MiniMax M2.7 scores 22.8 and Qwen3.5-35B-A3B scores 19.3, putting MiniMax M2.7 ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use MiniMax M2.7 and Qwen3.5-35B-A3B at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see MiniMax M2.7 and Qwen3.5-35B-A3B answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to MiniMax M2.7 and Qwen3.5-35B-A3B at the same time. Compare the answers side by side and keep the best one.