Gemma-SEA-LION-v4-27B-IT vs Qwen3-VL 30B-A3B vs Seed 1.6
Qwen3-VL 30B-A3B comes out ahead, 59 to 55 and 39 on our weighted score, and it is the cheaper option too.
AI Singapore
Gemma-SEA-LION-v4-27B-IT
39/100- ECI—
- Price$0.351 / $0.555
- Context128K
- Our pick
Alibaba (Qwen)Qwen3-VL 30B-A3B
59/100- ECI—
- Price$0.20 / $0.80
- Context131K
ByteDance SeedSeed 1.6
55/100- ECI—
- Price$0.119 / $1.19
- Context256K
Qwen3-VL 30B-A3B is our pick
Qwen3-VL 30B-A3B is the better all-round choice, scoring 59/100 against Seed 1.6 (55) and Gemma-SEA-LION-v4-27B-IT (39). It leads on price and inputs & features. Seed 1.6 wins on context window. 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-VL 30B-A3BQwen3-VL 30B-A3B $0.35 · Seed 1.6 $0.386 · Gemma-SEA-LION-v4-27B-IT $0.402 per 1M tokens (3:1 blend)
- Longest contextSeed 1.6Seed 1.6 256,000 · Qwen3-VL 30B-A3B 131,072 · Gemma-SEA-LION-v4-27B-IT 128,000 tokens
- Widest inputsQwen3-VL 30B-A3BGemma-SEA-LION-v4-27B-IT: Text · Qwen3-VL 30B-A3B: Text, Images · Seed 1.6: Text
- Self-hostingGemma-SEA-LION-v4-27B-IT and Qwen3-VL 30B-A3BPublishes downloadable weights
| Measure | Weight | Gemma-SEA-LION-v4-27B-IT | Qwen3-VL 30B-A3B | Seed 1.6 |
|---|---|---|---|---|
| Price | 50% | 69 | 72 | 69 |
| Inputs & features | 30% | 0 | 60 | 45 |
| Context window | 20% | 24 | 24 | 36 |
| Overall | 100% | 39/100 | 59/100 | 55/100 |
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 | Gemma-SEA-LION-v4-27B-ITAI Singapore | Qwen3-VL 30B-A3BAlibaba (Qwen) | Seed 1.6ByteDance Seed |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.351 | $0.20 | $0.119 (best) |
| Output | $0.555 (best) | $0.80 | $1.19 |
| Cached input | — | — | $0.024 |
| Blended (3:1) | $0.402 | $0.35 (best) | $0.386 |
| Long-context rate | Same rate | Same rate | Over 32K: $0.178 / $2.37 |
| Price source | Median of 2 providers | Official Alibaba API | Official Volcengine Ark API |
| Limits | |||
| Context window | 128,000 tokens | 131,072 tokens | 256,000 tokens (best) |
| Max output | 128,000 tokens (best) | 32,768 tokens | 64,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | Yesminimal · low · medium · high |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | — | qwen3-vl-30b-a3b | doubao-seed-1-6-251015 |
| API providers | 2 (best) | 1 | 2 (best) |
| Released | Sep 23, 2025 | Apr 2025 | Oct 15, 2025 |
| Knowledge cutoff | — | Apr 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemma-SEA-LION-v4-27B-IT$4.62
- Qwen3-VL 30B-A3B$3.60
- Seed 1.6$3.56
Which should you choose?
Which is better: Gemma-SEA-LION-v4-27B-IT, Qwen3-VL 30B-A3B or Seed 1.6?
Qwen3-VL 30B-A3B is the better all-round choice, scoring 59/100 against Seed 1.6 (55) and Gemma-SEA-LION-v4-27B-IT (39). It leads on price and inputs & features. Seed 1.6 wins on context window. 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, Gemma-SEA-LION-v4-27B-IT, Qwen3-VL 30B-A3B or Seed 1.6?
Qwen3-VL 30B-A3B is cheaper at $0.20 input / $0.80 output per million tokens (official Alibaba API price). Seed 1.6 costs $0.119 input / $1.19 output per million tokens (official Volcengine Ark API price); Gemma-SEA-LION-v4-27B-IT costs $0.351 input / $0.555 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.35 per million tokens for Qwen3-VL 30B-A3B versus $0.386 for Seed 1.6 (1.1× as much) and $0.402 for Gemma-SEA-LION-v4-27B-IT (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemma-SEA-LION-v4-27B-IT has not been scored yet, Qwen3-VL 30B-A3B has not been scored yet and Seed 1.6 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma-SEA-LION-v4-27B-IT, Qwen3-VL 30B-A3B and Seed 1.6 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Gemma-SEA-LION-v4-27B-IT does not support tool calling, which most coding agents need.
Which has the bigger context window?
Seed 1.6 has the largest context window at 256,000 tokens, against 131,072 for Qwen3-VL 30B-A3B and 128,000 for Gemma-SEA-LION-v4-27B-IT. Maximum output per response: Gemma-SEA-LION-v4-27B-IT up to 128,000, Qwen3-VL 30B-A3B up to 32,768, Seed 1.6 up to 64,000 tokens.
Which can read images, PDFs, audio or video?
Gemma-SEA-LION-v4-27B-IT accepts text; Qwen3-VL 30B-A3B accepts text and images; Seed 1.6 accepts text. Qwen3-VL 30B-A3B handles the widest range of inputs.
Are any of these open source?
Gemma-SEA-LION-v4-27B-IT and Qwen3-VL 30B-A3B publishes its weights and can be self-hosted; Seed 1.6 is proprietary.
Which is newer?
Seed 1.6 is the newest, released Oct 15, 2025. Gemma-SEA-LION-v4-27B-IT came out Sep 23, 2025; Qwen3-VL 30B-A3B came out Apr 2025. Knowledge cutoff: Qwen3-VL 30B-A3B Apr 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 Oct 4, 2026.
