Gemma 2 27B vs Llama-3.1-70B-Instruct vs Llama-3.2-90B-Vision-Instruct
Llama-3.2-90B-Vision-Instruct comes out ahead, 44 to 39 and 28 on our weighted score.
GoogleGemma 2 27B
28/100- ECI122.1
- Price$0.65 / $0.65
- Context8K
MetaLlama-3.1-70B-Instruct
39/100- ECI125.9
- Price$0.72 / $0.72
- Context128K
- Our pickMeta
Llama-3.2-90B-Vision-Instruct
44/100- ECI125.5
- Price—
- Context128K
Llama-3.2-90B-Vision-Instruct is our pick
Llama-3.2-90B-Vision-Instruct is the better all-round choice, scoring 44/100 against Llama-3.1-70B-Instruct (39) and Gemma 2 27B (28). It leads on inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityLlama-3.1-70B-InstructCapabilities Index (ECI): Llama-3.1-70B-Instruct 125.9 · Llama-3.2-90B-Vision-Instruct 125.5 · Gemma 2 27B 122.1
- Lowest priceGemma 2 27BGemma 2 27B $0.65 · Llama-3.1-70B-Instruct $0.72 per 1M tokens (3:1 blend) · Llama-3.2-90B-Vision-Instruct unpriced
- Longest contextLlama-3.1-70B-Instruct and Llama-3.2-90B-Vision-InstructLlama-3.1-70B-Instruct 128,000 · Llama-3.2-90B-Vision-Instruct 128,000 · Gemma 2 27B 8,192 tokens
- Widest inputsLlama-3.2-90B-Vision-InstructGemma 2 27B: Text · Llama-3.1-70B-Instruct: Text · Llama-3.2-90B-Vision-Instruct: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Gemma 2 27B | Llama-3.1-70B-Instruct | Llama-3.2-90B-Vision-Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 42 | 47 | 46 |
| Inputs & features | 20% | 0 | 25 | 50 |
| Context window | 13% | 0 | 24 | 24 |
| Overall | 100% | 28/100 | 39/100 | 44/100 |
Left out because at least one model lacks the data: 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 2 27BGoogle | Llama-3.1-70B-InstructMeta | Llama-3.2-90B-Vision-InstructMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 122.1 | 125.9 (best) | 125.5 |
| ECI rank | #152 of 165 | #149 of 165 (best) | #150 of 165 |
| GPQA DiamondGraduate-level science questions | 36.5% | 44.2% (best) | 41.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.4% | 3.6% (best) | 2.6% |
| Price per million tokens | |||
| Input | $0.65 (best) | $0.72 | — |
| Output | $0.65 (best) | $0.72 | — |
| Cached input | — | — | — |
| Blended (3:1) | $0.65 (best) | $0.72 | — |
| Long-context rate | Same rate | Same rate | — |
| Price source | Median of 3 providers | Median of 8 providers | — |
| Limits | |||
| Context window | 8,192 tokens | 128,000 tokens (best) | 128,000 tokens (best) |
| Max output | 2,048 tokens | 4,096 tokens (best) | 4,096 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | OpenLlama 3.2 Community License |
| API model ID | — | — | — |
| API providers | 3 | 8 (best) | 1 |
| Released | Jul 13, 2024 | Jul 23, 2024 | Sep 25, 2024 |
| Knowledge cutoff | Jun 30, 2024 | Dec 2023 | Dec 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemma 2 27B$7.80
- Llama-3.1-70B-Instruct$8.64
- Llama-3.2-90B-Vision-Instruct—
Which should you choose?
Which is better: Gemma 2 27B, Llama-3.1-70B-Instruct or Llama-3.2-90B-Vision-Instruct?
Llama-3.2-90B-Vision-Instruct is the better all-round choice, scoring 44/100 against Llama-3.1-70B-Instruct (39) and Gemma 2 27B (28). It leads on inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Gemma 2 27B, Llama-3.1-70B-Instruct or Llama-3.2-90B-Vision-Instruct?
Gemma 2 27B is cheaper at $0.65 input / $0.65 output per million tokens (median across 3 API providers). Llama-3.1-70B-Instruct costs $0.72 input / $0.72 output per million tokens (median across 8 API providers). At a typical mix of three input tokens to one output token, that is $0.65 per million tokens for Gemma 2 27B versus $0.72 for Llama-3.1-70B-Instruct (1.1× as much). Llama-3.2-90B-Vision-Instruct has no published per-token price.
Which scores higher on benchmarks?
Llama-3.1-70B-Instruct scores higher on the Capabilities Index (ECI): Llama-3.1-70B-Instruct 125.9 (#149 of 165), Llama-3.2-90B-Vision-Instruct 125.5 (#150 of 165) and Gemma 2 27B 122.1 (#152 of 165). The confidence ranges of the top two overlap (120.8–128.2 vs 120.3–127.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama-3.1-70B-Instruct 44.2%, Llama-3.2-90B-Vision-Instruct 41.0%, Gemma 2 27B 36.5%; OTIS Mock AIME 2024–2025 — Llama-3.1-70B-Instruct 3.6%, Llama-3.2-90B-Vision-Instruct 2.6%, Gemma 2 27B 1.4%.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 2 27B, Llama-3.1-70B-Instruct and Llama-3.2-90B-Vision-Instruct yet, so there is no like-for-like coding score. On overall capability, Llama-3.1-70B-Instruct leads, which tends to carry over to coding, but test on your own codebase. Note that Gemma 2 27B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Llama-3.1-70B-Instruct and Llama-3.2-90B-Vision-Instruct have the largest context windows (128,000 and 128,000 tokens), against 8,192 for Gemma 2 27B. Maximum output per response: Gemma 2 27B up to 2,048, Llama-3.1-70B-Instruct up to 4,096, Llama-3.2-90B-Vision-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Gemma 2 27B accepts text; Llama-3.1-70B-Instruct accepts text; Llama-3.2-90B-Vision-Instruct accepts text and images. Llama-3.2-90B-Vision-Instruct handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Llama 3.2 Community License), so you can self-host them.
Which is newer?
Llama-3.2-90B-Vision-Instruct is the newest, released Sep 25, 2024. Llama-3.1-70B-Instruct came out Jul 23, 2024; Gemma 2 27B came out Jul 13, 2024. Knowledge cutoff: Gemma 2 27B Jun 30, 2024, Llama-3.1-70B-Instruct Dec 2023, Llama-3.2-90B-Vision-Instruct Dec 2023.
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.
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