Gemma-SEA-LION-v4-27B-IT vs GPT-5-Codex
Too close to call on our weighted score (GPT-5-Codex 42, Gemma-SEA-LION-v4-27B-IT 39). The right pick depends on what you value most.
AI Singapore
Gemma-SEA-LION-v4-27B-IT
39/100- ECI—
- Price$0.351 / $0.555
- Context128K
OpenAIGPT-5-Codex
42/100- ECI—
- Price$1.25 / $10.00
- Context400K
Add a model
Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 3 points (GPT-5-Codex 42/100, Gemma-SEA-LION-v4-27B-IT 39/100), so choose by what matters most for your work: Gemma-SEA-LION-v4-27B-IT on price and GPT-5-Codex for long inputs. 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 priceGemma-SEA-LION-v4-27B-ITGemma-SEA-LION-v4-27B-IT $0.402 · GPT-5-Codex $3.44 per 1M tokens (3:1 blend)
- Longest contextGPT-5-CodexGPT-5-Codex 400,000 · Gemma-SEA-LION-v4-27B-IT 128,000 tokens
- Widest inputsGPT-5-CodexGemma-SEA-LION-v4-27B-IT: Text · GPT-5-Codex: Text, Images
- Self-hostingGemma-SEA-LION-v4-27B-ITPublishes downloadable weights
| Measure | Weight | Gemma-SEA-LION-v4-27B-IT | GPT-5-Codex |
|---|---|---|---|
| Price | 50% | 69 | 24 |
| Inputs & features | 30% | 0 | 70 |
| Context window | 20% | 24 | 44 |
| Overall | 100% | 39/100 | 42/100 |
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 | GPT-5-CodexOpenAI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.351 (best) | $1.25 |
| Output | $0.555 (best) | $10.00 |
| Cached input | — | — |
| Blended (3:1) | $0.402 (best) | $3.44 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 3 providers |
| Limits | ||
| Context window | 128,000 tokens | 400,000 tokens (best) |
| Max output | 128,000 tokens | 128,000 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | Yes |
| Tool calling | No | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | Open | Proprietary |
| API model ID | — | — |
| API providers | 2 | 3 (best) |
| Released | Sep 23, 2025 | Sep 15, 2025 |
| Knowledge cutoff | — | Sep 30, 2024 |
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
- GPT-5-Codex$32.50
Which should you choose?
Which is better: Gemma-SEA-LION-v4-27B-IT or GPT-5-Codex?
It is close. Our weighted score puts them within 3 points (GPT-5-Codex 42/100, Gemma-SEA-LION-v4-27B-IT 39/100), so choose by what matters most for your work: Gemma-SEA-LION-v4-27B-IT on price and GPT-5-Codex for long inputs. 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 or GPT-5-Codex?
Gemma-SEA-LION-v4-27B-IT is cheaper at $0.351 input / $0.555 output per million tokens (median across 2 API providers). GPT-5-Codex costs $1.25 input / $10.00 output per million tokens (median across 3 API providers). At a typical mix of three input tokens to one output token, that is $0.402 per million tokens for Gemma-SEA-LION-v4-27B-IT versus $3.44 for GPT-5-Codex (8.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Gemma-SEA-LION-v4-27B-IT has not been scored yet and GPT-5-Codex 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 and GPT-5-Codex 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?
GPT-5-Codex has the largest context window at 400,000 tokens, against 128,000 for Gemma-SEA-LION-v4-27B-IT. Maximum output per response: Gemma-SEA-LION-v4-27B-IT up to 128,000, GPT-5-Codex up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Gemma-SEA-LION-v4-27B-IT accepts text; GPT-5-Codex accepts text and images. GPT-5-Codex handles the widest range of inputs.
Are any of these open source?
Gemma-SEA-LION-v4-27B-IT publishes its weights and can be self-hosted; GPT-5-Codex is proprietary.
Which is newer?
Gemma-SEA-LION-v4-27B-IT is the newest, released Sep 23, 2025. GPT-5-Codex came out Sep 15, 2025. Knowledge cutoff: GPT-5-Codex Sep 30, 2024.
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.
Related comparisons
- Add Seed 1.6Three-way comparison
- Gemma-SEA-LION-v4-27B-IT vs Seed 1.6ByteDance Seed
- Gemma-SEA-LION-v4-27B-IT vs GLM-4.5-AirZ.ai (Zhipu)
- Gemma-SEA-LION-v4-27B-IT vs Qwen3-VL PlusAlibaba (Qwen)
- Gemma-SEA-LION-v4-27B-IT vs MiniMax-M2MiniMax
- GPT-5-Codex vs Gemini 2.5 Computer Use PreviewGoogle
- GPT-5-Codex vs Jamba LargeAI21 Labs
