Gemma 2 27B vs Llama-3.1-8B-Instruct vs Mistral Large
Llama-3.1-8B-Instruct comes out ahead, 49 to 44 and 35 on our weighted score, and it is the cheaper option too.
GoogleGemma 2 27B
35/100- ECI122.1
- Price$0.65 / $0.65
- Context8K
- Our pick
MetaLlama-3.1-8B-Instruct
49/100- ECI116.4
- Price$0.06 / $0.08
- Context128K
Mistral AIMistral Large
44/100- ECI122.0
- Price$0.50 / $1.50
- Context128K
Llama-3.1-8B-Instruct is our pick
Llama-3.1-8B-Instruct is the better all-round choice, scoring 49/100 against Mistral Large (44) and Gemma 2 27B (35). It leads on price. Mistral Large wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGemma 2 27BCapabilities Index (ECI): Gemma 2 27B 122.1 · Mistral Large 122.0 · Llama-3.1-8B-Instruct 116.4
- Lowest priceLlama-3.1-8B-InstructLlama-3.1-8B-Instruct $0.065 · Gemma 2 27B $0.65 · Mistral Large $0.75 per 1M tokens (3:1 blend)
- Longest contextLlama-3.1-8B-Instruct and Mistral LargeLlama-3.1-8B-Instruct 128,000 · Mistral Large 128,000 · Gemma 2 27B 8,192 tokens
- Widest inputsMistral LargeGemma 2 27B: Text · Llama-3.1-8B-Instruct: Text · Mistral Large: Text, PDFs
- Self-hostingGemma 2 27B and Llama-3.1-8B-InstructPublishes downloadable weights
| Measure | Weight | Gemma 2 27B | Llama-3.1-8B-Instruct | Mistral Large |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 42 | 35 | 42 |
| Price | 25% | 56 | 100 | 53 |
| Inputs & features | 15% | 0 | 25 | 45 |
| Context window | 10% | 0 | 24 | 24 |
| Overall | 100% | 35/100 | 49/100 | 44/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemma 2 27BGoogle | Llama-3.1-8B-InstructMeta | Mistral LargeMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 122.1 (best) | 116.4 | 122.0 |
| ECI rank | #152 of 165 (best) | #162 of 165 | #153 of 165 |
| GPQA DiamondGraduate-level science questions | 36.5% | 27.0% | 38.8% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.4% | 1.7% | 1.9% (best) |
| Price per million tokens | |||
| Input | $0.65 | $0.06 (best) | $0.50 |
| Output | $0.65 | $0.08 (best) | $1.50 |
| Cached input | — | — | $0.05 |
| Blended (3:1) | $0.65 | $0.065 (best) | $0.75 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Median of 17 providers | Official Mistral API |
| Limits | |||
| Context window | 8,192 tokens | 128,000 tokens (best) | 128,000 tokens (best) |
| Max output | 2,048 tokens | 4,096 tokens | 102,400 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | — | — | mistral-large-latest |
| API providers | 3 | 18 (best) | 11 |
| Released | Jul 13, 2024 | Jul 23, 2024 | Feb 26, 2024 |
| Knowledge cutoff | Jun 30, 2024 | Dec 2023 | Nov 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 2 27B$7.80
- Llama-3.1-8B-Instruct$0.76
- Mistral Large$8.00
Which should you choose?
Which is better: Gemma 2 27B, Llama-3.1-8B-Instruct or Mistral Large?
Llama-3.1-8B-Instruct is the better all-round choice, scoring 49/100 against Mistral Large (44) and Gemma 2 27B (35). It leads on price. Mistral Large wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Gemma 2 27B, Llama-3.1-8B-Instruct or Mistral Large?
Llama-3.1-8B-Instruct is cheaper at $0.06 input / $0.08 output per million tokens (median across 17 API providers). Gemma 2 27B costs $0.65 input / $0.65 output per million tokens (median across 3 API providers); Mistral Large costs $0.50 input / $1.50 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.065 per million tokens for Llama-3.1-8B-Instruct versus $0.65 for Gemma 2 27B (10× as much) and $0.75 for Mistral Large (12× as much).
Which scores higher on benchmarks?
Gemma 2 27B scores higher on the Capabilities Index (ECI): Gemma 2 27B 122.1 (#152 of 165), Mistral Large 122.0 (#153 of 165) and Llama-3.1-8B-Instruct 116.4 (#162 of 165). The confidence ranges of the top two overlap (115.8–124.1 vs 115.7–124.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 38.8%, Gemma 2 27B 36.5%, Llama-3.1-8B-Instruct 27.0%; OTIS Mock AIME 2024–2025 — Mistral Large 1.9%, Llama-3.1-8B-Instruct 1.7%, Gemma 2 27B 1.4%.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 2 27B, Llama-3.1-8B-Instruct and Mistral Large yet, so there is no like-for-like coding score. On overall capability, Gemma 2 27B 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-3.1-8B-Instruct and Mistral Large 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-3.1-8B-Instruct up to 4,096, Mistral Large up to 102,400 tokens.
Which can read images, PDFs, audio or video?
Gemma 2 27B accepts text; Llama-3.1-8B-Instruct accepts text; Mistral Large accepts text and PDFs. Mistral Large handles the widest range of inputs.
Are any of these open source?
Gemma 2 27B and Llama-3.1-8B-Instruct publishes its weights and can be self-hosted; Mistral Large is proprietary.
Which is newer?
Llama-3.1-8B-Instruct is the newest, released Jul 23, 2024. Gemma 2 27B came out Jul 13, 2024; Mistral Large came out Feb 26, 2024. Knowledge cutoff: Gemma 2 27B Jun 30, 2024, Llama-3.1-8B-Instruct Dec 2023, Mistral Large Nov 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 Nov 2, 2026.
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