Gemma 4 E4B IT vs GPT-5.3 Chat vs Qwen3.5 0.8B
Qwen3.5 0.8B comes out ahead, 57 to 52 and 40 on our weighted score.
GoogleGemma 4 E4B IT
52/100- ECI—
- Price$0.02 / $0.10
- Context131K
OpenAIGPT-5.3 Chat
40/100- ECI—
- Price$1.75 / $14.00
- Context128K
- Our pick
Alibaba (Qwen)Qwen3.5 0.8B
57/100- ECI—
- Price—
- Context262K
Qwen3.5 0.8B is our pick
Qwen3.5 0.8B is the better all-round choice, scoring 57/100 against Gemma 4 E4B IT (52) and GPT-5.3 Chat (40). It leads on context window. The score weighs inputs & features 60%, context window 40%. 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 priceGemma 4 E4B ITGemma 4 E4B IT $0.04 · GPT-5.3 Chat $4.81 per 1M tokens (3:1 blend) · Qwen3.5 0.8B unpriced
- Longest contextQwen3.5 0.8BQwen3.5 0.8B 262,144 · Gemma 4 E4B IT 131,072 · GPT-5.3 Chat 128,000 tokens
- Widest inputsGemma 4 E4B IT and Qwen3.5 0.8BGemma 4 E4B IT: Text, Images, Audio · GPT-5.3 Chat: Text, Images · Qwen3.5 0.8B: Text, Images, Video
- Self-hostingGemma 4 E4B IT and Qwen3.5 0.8BPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Gemma 4 E4B IT | GPT-5.3 Chat | Qwen3.5 0.8B |
|---|---|---|---|---|
| Inputs & features | 60% | 70 | 50 | 70 |
| Context window | 40% | 25 | 24 | 37 |
| Overall | 100% | 52/100 | 40/100 | 57/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemma 4 E4B ITGoogle | GPT-5.3 ChatOpenAI | Qwen3.5 0.8BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.02 (best) | $1.75 | — |
| Output | $0.10 (best) | $14.00 | — |
| Cached input | — | — | — |
| Blended (3:1) | $0.04 (best) | $4.81 | — |
| Long-context rate | Same rate | Same rate | — |
| Price source | Median of 1 providers | Median of 4 providers | — |
| Limits | |||
| Context window | 131,072 tokens | 128,000 tokens | 262,144 tokens (best) |
| Max output | 8,192 tokens | 16,384 tokens | 81,920 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | Yes | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | OpenApache-2.0 |
| API model ID | — | — | — |
| API providers | 2 | 4 (best) | 1 |
| Released | Apr 2, 2026 | Mar 3, 2026 | Mar 2, 2026 |
| Knowledge cutoff | — | Aug 31, 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 4 E4B IT$0.40
- GPT-5.3 Chat$45.50
- Qwen3.5 0.8B—
Which should you choose?
Which is better: Gemma 4 E4B IT, GPT-5.3 Chat or Qwen3.5 0.8B?
Qwen3.5 0.8B is the better all-round choice, scoring 57/100 against Gemma 4 E4B IT (52) and GPT-5.3 Chat (40). It leads on context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Gemma 4 E4B IT, GPT-5.3 Chat or Qwen3.5 0.8B?
Gemma 4 E4B IT is cheaper at $0.02 input / $0.10 output per million tokens (median across 1 API provider). GPT-5.3 Chat costs $1.75 input / $14.00 output per million tokens (median across 4 API providers). At a typical mix of three input tokens to one output token, that is $0.04 per million tokens for Gemma 4 E4B IT versus $4.81 for GPT-5.3 Chat (120× as much). Qwen3.5 0.8B has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemma 4 E4B IT has not been scored yet, GPT-5.3 Chat has not been scored yet and Qwen3.5 0.8B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 4 E4B IT, GPT-5.3 Chat and Qwen3.5 0.8B 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?
Qwen3.5 0.8B has the largest context window at 262,144 tokens, against 131,072 for Gemma 4 E4B IT and 128,000 for GPT-5.3 Chat. Maximum output per response: Gemma 4 E4B IT up to 8,192, GPT-5.3 Chat up to 16,384, Qwen3.5 0.8B up to 81,920 tokens.
Which can read images, PDFs, audio or video?
Gemma 4 E4B IT accepts text, images and audio; GPT-5.3 Chat accepts text and images; Qwen3.5 0.8B accepts text, images and video. Gemma 4 E4B IT handles the widest range of inputs.
Are any of these open source?
Gemma 4 E4B IT and Qwen3.5 0.8B publishes its weights (Apache-2.0) and can be self-hosted; GPT-5.3 Chat is proprietary.
Which is newer?
Gemma 4 E4B IT is the newest, released Apr 2, 2026. GPT-5.3 Chat came out Mar 3, 2026; Qwen3.5 0.8B came out Mar 2, 2026. Knowledge cutoff: GPT-5.3 Chat Aug 31, 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.
