AI model comparison
LFM2.5-2.6B vs Qwen3 VL 30B A3B Instruct
Side by side comparison of LFM2.5-2.6B and Qwen3 VL 30B A3B Instruct on pricing, benchmark scores, context window, and more.
LFM2.5-2.6B is a compact reasoning model from Liquid AI. It is suited for agent workflows, data extraction, RAG, and long-context processing.
- Input / 1M
- $0.35
- Output / 1M
- $0.50
- Context
- 128K
Qwen3-VL-30B-A3B-Instruct is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Instruct variant optimizes instruction-following for general multimodal tasks.
- Input / 1M
- $0.15
- Output / 1M
- $0.60
- Context
- 262K
Comparing image generators? Compare image models
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
Qwen3 VL 30B A3B Instruct
1.6x cheaper for a typical chat
Higher intelligence score
LFM2.5-2.6B
8.4 vs 7.9 on Artificial Analysis
Larger context window
Qwen3 VL 30B A3B Instruct
262K vs 128K tokens
Newer release
LFM2.5-2.6B
Released August 11, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
LFM2.5-2.6B8.4Qwen3 VL 30B A3B Instruct7.9Coding index
LFM2.5-2.6B7.7Qwen3 VL 30B A3B InstructNot availableAgentic index
LFM2.5-2.6BNot availableQwen3 VL 30B A3B InstructNot availablePricing
LFM2.5-2.6B vs Qwen3 VL 30B A3B Instruct API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | LFM2.5-2.6B | Qwen3 VL 30B A3B Instruct |
|---|---|---|
| Input tokensPer 1M tokens | $0.35 | $0.15 |
| Output tokensPer 1M tokens | $0.50 | $0.60 |
| Cached input (read)Per 1M tokens | $0.04 | Not available |
| 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
LFM2.5-2.6B$0.95Qwen3 VL 30B A3B Instruct$0.60Coding task
30K in, 4K out
LFM2.5-2.6B$12.50$3.20 cachedQwen3 VL 30B A3B Instruct$6.90Long document summary
150K in, 2K out
LFM2.5-2.6B$53.50$7 cachedQwen3 VL 30B A3B Instruct$23.70Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | LFM2.5-2.6B | Qwen3 VL 30B A3B Instruct |
|---|---|---|
| Context window | 128K tokens | 262K tokens |
| Max output | 8K tokens | 16K tokens |
| Input types | Text | Image, Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | August 11, 2026 | October 6, 2025 |
Features
Supported features
API features available for each model.
| Metric | LFM2.5-2.6B | Qwen3 VL 30B A3B Instruct |
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Not supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Not supported |
Keep exploring
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Our take
Qwen3 VL 30B A3B Instruct is 1.6x cheaper for a typical chat. LFM2.5-2.6B scores higher on the Artificial Analysis Intelligence Index (8.4 vs 7.9). Qwen3 VL 30B A3B Instruct has the larger context window (262K vs 128K 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 LFM2.5-2.6B or Qwen3 VL 30B A3B Instruct cheaper?
Qwen3 VL 30B A3B Instruct is cheaper for a typical chat (2K input tokens and 500 output tokens). Qwen3 VL 30B A3B Instruct costs $0.15 per 1M input tokens and $0.60 per 1M output tokens, while LFM2.5-2.6B costs $0.35 per 1M input tokens and $0.50 per 1M output tokens.
Which has a bigger context window, LFM2.5-2.6B or Qwen3 VL 30B A3B Instruct?
Qwen3 VL 30B A3B Instruct supports up to 262K tokens of context, compared with 128K for LFM2.5-2.6B.
Is LFM2.5-2.6B smarter than Qwen3 VL 30B A3B Instruct?
On the Artificial Analysis Intelligence Index, LFM2.5-2.6B scores 8.4 and Qwen3 VL 30B A3B Instruct scores 7.9, putting LFM2.5-2.6B ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use LFM2.5-2.6B and Qwen3 VL 30B A3B Instruct at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see LFM2.5-2.6B and Qwen3 VL 30B A3B Instruct answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to LFM2.5-2.6B and Qwen3 VL 30B A3B Instruct at the same time. Compare the answers side by side and keep the best one.