GPT-4.1 nano vs GPT-5.4 nano vs Gemma 3 27B IT
GPT-5.4 nano comes out ahead, 68 to 63 and 60 on our weighted score, though Gemma 3 27B IT is 4.2× cheaper per token.
OpenAIGPT-4.1 nano
63/100- ECI129.6
- Price$0.10 / $0.40
- Context1.05M
- Our pickOpenAI
GPT-5.4 nano
68/100- ECI145.8
- Price$0.20 / $1.25
- Context400K
GoogleGemma 3 27B IT
60/100- ECI130.0
- Price$0.08 / $0.20
- Context131K
GPT-5.4 nano is our pick
GPT-5.4 nano is the better all-round choice, scoring 68/100 against GPT-4.1 nano (63) and Gemma 3 27B IT (60). It leads on capability and inputs & features. GPT-4.1 nano wins on context window. Gemma 3 27B IT wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-5.4 nanoCapabilities Index (ECI): GPT-5.4 nano 145.8 · Gemma 3 27B IT 130.0 · GPT-4.1 nano 129.6
- Lowest priceGemma 3 27B ITGemma 3 27B IT $0.11 · GPT-4.1 nano $0.175 · GPT-5.4 nano $0.463 per 1M tokens (3:1 blend)
- Longest contextGPT-4.1 nanoGPT-4.1 nano 1,047,576 · GPT-5.4 nano 400,000 · Gemma 3 27B IT 131,072 tokens
- Widest inputsSame inputsGPT-4.1 nano: Text, Images · GPT-5.4 nano: Text, Images · Gemma 3 27B IT: Text, Images
- Self-hostingGemma 3 27B ITPublishes downloadable weights
| Measure | Weight | GPT-4.1 nano | GPT-5.4 nano | Gemma 3 27B IT |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 52 | 73 | 53 |
| Price | 25% | 86 | 66 | 95 |
| Inputs & features | 15% | 60 | 70 | 50 |
| Context window | 10% | 61 | 44 | 24 |
| Overall | 100% | 63/100 | 68/100 | 60/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GPT-4.1 nanoOpenAI | GPT-5.4 nanoOpenAI | Gemma 3 27B ITGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 129.6 | 145.8 (best) | 130.0 |
| ECI rank | #127 of 148 | #75 of 148 (best) | #125 of 148 |
| GPQA DiamondGraduate-level science questions | 48.9% | 78.5% (best) | 47.7% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 44.9% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 28.9% | 87.8% (best) | 22.5% |
| SimpleQA VerifiedShort factual questions | 6.0% | 11.7% (best) | — |
| Price per million tokens | |||
| Input | $0.10 | $0.20 | $0.08 (best) |
| Output | $0.40 | $1.25 | $0.20 (best) |
| Cached input | $0.025 | $0.02 (best) | — |
| Blended (3:1) | $0.175 | $0.463 | $0.11 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Official OpenAI API | Median of 9 providers |
| Limits | |||
| Context window | 1,047,576 tokens (best) | 400,000 tokens | 131,072 tokens |
| Max output | 32,768 tokens | 128,000 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yeslow · medium · high · xhigh | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | gpt-4.1-nano | gpt-5.4-nano | — |
| API providers | 20 | 26 (best) | 10 |
| Released | Apr 14, 2025 | Mar 17, 2026 | Mar 12, 2025 |
| Knowledge cutoff | Apr 2024 | Aug 31, 2025 | Aug 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GPT-4.1 nano$1.80
- GPT-5.4 nano$4.50
- Gemma 3 27B IT$1.20
Which should you choose?
Which is better: GPT-4.1 nano, GPT-5.4 nano or Gemma 3 27B IT?
GPT-5.4 nano is the better all-round choice, scoring 68/100 against GPT-4.1 nano (63) and Gemma 3 27B IT (60). It leads on capability and inputs & features. GPT-4.1 nano wins on context window. Gemma 3 27B IT wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GPT-4.1 nano, GPT-5.4 nano or Gemma 3 27B IT?
Gemma 3 27B IT is cheaper at $0.08 input / $0.20 output per million tokens (median across 9 API providers). GPT-4.1 nano costs $0.10 input / $0.40 output per million tokens (official OpenAI API price); GPT-5.4 nano costs $0.20 input / $1.25 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.11 per million tokens for Gemma 3 27B IT versus $0.175 for GPT-4.1 nano (1.6× as much) and $0.463 for GPT-5.4 nano (4.2× as much).
Which scores higher on benchmarks?
GPT-5.4 nano scores higher on the Capabilities Index (ECI): GPT-5.4 nano 145.8 (#75 of 148), Gemma 3 27B IT 130.0 (#125 of 148) and GPT-4.1 nano 129.6 (#127 of 148). Their confidence ranges do not overlap (143.2–147.7 vs 124.1–132.2), so the gap is a real one. On individual benchmarks: GPQA Diamond — GPT-5.4 nano 78.5%, GPT-4.1 nano 48.9%, Gemma 3 27B IT 47.7%; OTIS Mock AIME 2024–2025 — GPT-5.4 nano 87.8%, GPT-4.1 nano 28.9%, Gemma 3 27B IT 22.5%.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-4.1 nano, GPT-5.4 nano and Gemma 3 27B IT yet, so there is no like-for-like coding score. On overall capability, GPT-5.4 nano leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-4.1 nano has the largest context window at 1,047,576 tokens, against 400,000 for GPT-5.4 nano and 131,072 for Gemma 3 27B IT. Maximum output per response: GPT-4.1 nano up to 32,768, GPT-5.4 nano up to 128,000, Gemma 3 27B IT up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GPT-4.1 nano accepts text and images; GPT-5.4 nano accepts text and images; Gemma 3 27B IT accepts text and images. They handle the same number of input types.
Are any of these open source?
Gemma 3 27B IT publishes its weights and can be self-hosted; GPT-4.1 nano and GPT-5.4 nano is proprietary.
Which is newer?
GPT-5.4 nano is the newest, released Mar 17, 2026. GPT-4.1 nano came out Apr 14, 2025; Gemma 3 27B IT came out Mar 12, 2025. Knowledge cutoff: GPT-4.1 nano Apr 2024, GPT-5.4 nano Aug 31, 2025, Gemma 3 27B IT Aug 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.
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