DiffusionGemma 26B A4B IT vs LFM2 24B A2B vs Qwen3.5 4B
Qwen3.5 4B comes out ahead, 78 to 75 and 58 on our weighted score, and it is the cheaper option too.
GoogleDiffusionGemma 26B A4B IT
75/100- ECI—
- Price$0.05 / $0.15
- Context262K
Liquid AILFM2 24B A2B
58/100- ECI—
- Price$0.03 / $0.12
- Context33K
- Our pick
Alibaba (Qwen)Qwen3.5 4B
78/100- ECI—
- Price$0.04 / $0.07
- Context262K
Qwen3.5 4B is our pick
Qwen3.5 4B is the better all-round choice, scoring 78/100 against DiffusionGemma 26B A4B IT (75) and LFM2 24B A2B (58). It leads on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceQwen3.5 4BQwen3.5 4B $0.048 · LFM2 24B A2B $0.052 · DiffusionGemma 26B A4B IT $0.075 per 1M tokens (3:1 blend)
- Longest contextDiffusionGemma 26B A4B IT and Qwen3.5 4BDiffusionGemma 26B A4B IT 262,144 · Qwen3.5 4B 262,144 · LFM2 24B A2B 32,768 tokens
- Widest inputsQwen3.5 4BDiffusionGemma 26B A4B IT: Text, Images · LFM2 24B A2B: Text · Qwen3.5 4B: Text, Images, Video
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DiffusionGemma 26B A4B IT | LFM2 24B A2B | Qwen3.5 4B |
|---|---|---|---|---|
| Price | 50% | 99 | 100 | 100 |
| Inputs & features | 30% | 60 | 25 | 70 |
| Context window | 20% | 37 | 0 | 37 |
| Overall | 100% | 75/100 | 58/100 | 78/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DiffusionGemma 26B A4B ITGoogle | LFM2 24B A2BLiquid AI | Qwen3.5 4BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | — | 55.8% |
| Price per million tokens | |||
| Input | $0.05 | $0.03 (best) | $0.04 |
| Output | $0.15 | $0.12 | $0.07 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.075 | $0.052 | $0.048 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 1 providers | Median of 3 providers |
| Limits | |||
| Context window | 262,144 tokens (best) | 32,768 tokens | 262,144 tokens (best) |
| Max output | 32,768 tokens | 32,768 tokens | 81,920 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache 2.0 | OpenLFM Open License v1.0 | OpenApache-2.0 |
| API model ID | — | — | — |
| API providers | 2 | 1 | 5 (best) |
| Released | Jun 9, 2026 | Feb 24, 2026 | Mar 2, 2026 |
| Knowledge cutoff | Jan 2025 | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- DiffusionGemma 26B A4B IT$0.80
- LFM2 24B A2B$0.54
- Qwen3.5 4B$0.54
Which should you choose?
Which is better: DiffusionGemma 26B A4B IT, LFM2 24B A2B or Qwen3.5 4B?
Qwen3.5 4B is the better all-round choice, scoring 78/100 against DiffusionGemma 26B A4B IT (75) and LFM2 24B A2B (58). It leads on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, DiffusionGemma 26B A4B IT, LFM2 24B A2B or Qwen3.5 4B?
Qwen3.5 4B is cheaper at $0.04 input / $0.07 output per million tokens (median across 3 API providers). LFM2 24B A2B costs $0.03 input / $0.12 output per million tokens (median across 1 API provider); DiffusionGemma 26B A4B IT costs $0.05 input / $0.15 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.048 per million tokens for Qwen3.5 4B versus $0.052 for LFM2 24B A2B (1.1× as much) and $0.075 for DiffusionGemma 26B A4B IT (1.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. DiffusionGemma 26B A4B IT has not been scored yet, LFM2 24B A2B has not been scored yet and Qwen3.5 4B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for DiffusionGemma 26B A4B IT, LFM2 24B A2B and Qwen3.5 4B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
DiffusionGemma 26B A4B IT and Qwen3.5 4B have the largest context windows (262,144 and 262,144 tokens), against 32,768 for LFM2 24B A2B. Maximum output per response: DiffusionGemma 26B A4B IT up to 32,768, LFM2 24B A2B up to 32,768, Qwen3.5 4B up to 81,920 tokens.
Which can read images, PDFs, audio or video?
DiffusionGemma 26B A4B IT accepts text and images; LFM2 24B A2B accepts text; Qwen3.5 4B accepts text, images and video. Qwen3.5 4B handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Apache 2.0, LFM Open License v1.0 and Apache-2.0), so you can self-host them.
Which is newer?
DiffusionGemma 26B A4B IT is the newest, released Jun 9, 2026. Qwen3.5 4B came out Mar 2, 2026; LFM2 24B A2B came out Feb 24, 2026. Knowledge cutoff: DiffusionGemma 26B A4B IT Jan 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.
