Gemma 2 27B vs Llama-3.1-70B-Instruct vs Mixtral 8x7B Instruct v0.1
Llama-3.1-70B-Instruct comes out ahead, 43 to 35 and 34 on our weighted score, though Mixtral 8x7B Instruct v0.1 is 34% cheaper per token.
Google
Gemma 2 27B
35/100- ECI122.1
- Price$0.65 / $0.65
- Context8K
- Our pick
Meta
Llama-3.1-70B-Instruct
43/100- ECI125.9
- Price$0.72 / $0.72
- Context128K
Mistral AI
Mixtral 8x7B Instruct v0.1
34/100- ECI118.4
- Price$0.444 / $0.579
- Context33K
Llama-3.1-70B-Instruct is our pick
Llama-3.1-70B-Instruct is the better all-round choice, scoring 43/100 against Gemma 2 27B (35) and Mixtral 8x7B Instruct v0.1 (34). It leads on capability, inputs & features and context window. Mixtral 8x7B Instruct v0.1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityLlama-3.1-70B-InstructCapabilities Index (ECI): Llama-3.1-70B-Instruct 125.9 · Gemma 2 27B 122.1 · Mixtral 8x7B Instruct v0.1 118.4
- Lowest priceMixtral 8x7B Instruct v0.1Mixtral 8x7B Instruct v0.1 $0.478 · Gemma 2 27B $0.65 · Llama-3.1-70B-Instruct $0.72 per 1M tokens (3:1 blend)
- Longest contextLlama-3.1-70B-InstructLlama-3.1-70B-Instruct 128,000 · Mixtral 8x7B Instruct v0.1 32,768 · Gemma 2 27B 8,192 tokens
- Widest inputsSame inputsGemma 2 27B: Text · Llama-3.1-70B-Instruct: Text · Mixtral 8x7B Instruct v0.1: Text
- 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 | Mixtral 8x7B Instruct v0.1 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 42 | 47 | 38 |
| Price | 25% | 56 | 54 | 62 |
| Inputs & features | 15% | 0 | 25 | 0 |
| Context window | 10% | 0 | 24 | 0 |
| Overall | 100% | 35/100 | 43/100 | 34/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 122.1 | 125.9 (best) | 118.4 |
| ECI rank | #152 of 165 | #149 of 165 (best) | #160 of 165 |
| GPQA DiamondGraduate-level science questions | 36.5% | 44.2% (best) | 30.6% |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.4% | 3.6% (best) | — |
| Price per million tokens | |||
| Input | $0.65 | $0.72 | $0.444 (best) |
| Output | $0.65 | $0.72 | $0.579 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.65 | $0.72 | $0.478 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Median of 8 providers | Median of 2 providers |
| Limits | |||
| Context window | 8,192 tokens | 128,000 tokens (best) | 32,768 tokens |
| Max output | 2,048 tokens | 4,096 tokens | 32,768 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | No | Yes | No |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | OpenApache 2.0 |
| API model ID | — | — | — |
| API providers | 3 | 8 (best) | 2 |
| Released | Jul 13, 2024 | Jul 23, 2024 | Dec 11, 2023 |
| Knowledge cutoff | Jun 30, 2024 | 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
Mixtral 8x7B Instruct v0.1$5.60
Which should you choose?
Which is better: Gemma 2 27B, Llama-3.1-70B-Instruct or Mixtral 8x7B Instruct v0.1?
Llama-3.1-70B-Instruct is the better all-round choice, scoring 43/100 against Gemma 2 27B (35) and Mixtral 8x7B Instruct v0.1 (34). It leads on capability, inputs & features and context window. Mixtral 8x7B Instruct v0.1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Gemma 2 27B, Llama-3.1-70B-Instruct or Mixtral 8x7B Instruct v0.1?
Mixtral 8x7B Instruct v0.1 is cheaper at $0.444 input / $0.579 output per million tokens (median across 2 API providers). Gemma 2 27B costs $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 $0.478 per million tokens for Mixtral 8x7B Instruct v0.1 versus $0.65 for Gemma 2 27B (1.4× as much) and $0.72 for Llama-3.1-70B-Instruct (1.5× as much).
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), Gemma 2 27B 122.1 (#152 of 165) and Mixtral 8x7B Instruct v0.1 118.4 (#160 of 165). The confidence ranges of the top two overlap (120.8–128.2 vs 115.8–124.1), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama-3.1-70B-Instruct 44.2%, Gemma 2 27B 36.5%, Mixtral 8x7B Instruct v0.1 30.6%.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 2 27B, Llama-3.1-70B-Instruct and Mixtral 8x7B Instruct v0.1 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 and Mixtral 8x7B Instruct v0.1 does not support tool calling, which most coding agents need.
Which has the bigger context window?
Llama-3.1-70B-Instruct has the largest context window at 128,000 tokens, against 32,768 for Mixtral 8x7B Instruct v0.1 and 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, Mixtral 8x7B Instruct v0.1 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Gemma 2 27B accepts text; Llama-3.1-70B-Instruct accepts text; Mixtral 8x7B Instruct v0.1 accepts text. They handle the same number of input types.
Are any of these open source?
Yes, all three publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
Llama-3.1-70B-Instruct is the newest, released Jul 23, 2024. Gemma 2 27B came out Jul 13, 2024; Mixtral 8x7B Instruct v0.1 came out Dec 11, 2023. Knowledge cutoff: Gemma 2 27B Jun 30, 2024, Llama-3.1-70B-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.