Gemma 2 27B vs GPT-4o vs Mixtral 8x22B Instruct
GPT-4o comes out ahead, 43 to 35 and 34 on our weighted score, though Gemma 2 27B is 6.7× cheaper per token.
GoogleGemma 2 27B
35/100- ECI122.1
- Price$0.65 / $0.65
- Context8K
- Our pick
OpenAIGPT-4o
43/100- ECI129.0
- Price$2.50 / $10.00
- Context128K
Mistral AIMixtral 8x22B Instruct
34/100- ECI122.0
- Price$2.00 / $6.00
- Context66K
GPT-4o is our pick
GPT-4o is the better all-round choice, scoring 43/100 against Gemma 2 27B (35) and Mixtral 8x22B Instruct (34). It leads on capability, inputs & features and context window. Gemma 2 27B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-4oCapabilities Index (ECI): GPT-4o 129.0 · Gemma 2 27B 122.1 · Mixtral 8x22B Instruct 122.0
- Lowest priceGemma 2 27BGemma 2 27B $0.65 · Mixtral 8x22B Instruct $3.00 · GPT-4o $4.38 per 1M tokens (3:1 blend)
- Longest contextGPT-4oGPT-4o 128,000 · Mixtral 8x22B Instruct 65,536 · Gemma 2 27B 8,192 tokens
- Widest inputsGPT-4oGemma 2 27B: Text · GPT-4o: Text, Images, PDFs · Mixtral 8x22B Instruct: Text, PDFs
- Self-hostingGemma 2 27B and Mixtral 8x22B InstructPublishes downloadable weights
| Measure | Weight | Gemma 2 27B | GPT-4o | Mixtral 8x22B Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 42 | 51 | 42 |
| Price | 25% | 56 | 19 | 26 |
| Inputs & features | 15% | 0 | 70 | 35 |
| Context window | 10% | 0 | 24 | 12 |
| 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 | Gemma 2 27BGoogle | GPT-4oOpenAI | Mixtral 8x22B InstructMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 122.1 | 129.0 (best) | 122.0 |
| ECI rank | #152 of 165 | #141 of 165 (best) | #155 of 165 |
| GPQA DiamondGraduate-level science questions | 36.5% | 48.9% (best) | 34.1% |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.4% | 6.3% (best) | — |
| Price per million tokens | |||
| Input | $0.65 (best) | $2.50 | $2.00 |
| Output | $0.65 (best) | $10.00 | $6.00 |
| Cached input | — | $1.25 | — |
| Blended (3:1) | $0.65 (best) | $4.38 | $3.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Official OpenAI API | Median of 5 providers |
| Limits | |||
| Context window | 8,192 tokens | 128,000 tokens (best) | 65,536 tokens |
| Max output | 2,048 tokens | 16,384 tokens | 52,428 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | No | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | — | gpt-4o | — |
| API providers | 3 | 26 (best) | 5 |
| Released | Jul 13, 2024 | May 13, 2024 | Apr 17, 2024 |
| Knowledge cutoff | Jun 30, 2024 | Sep 2023 | Jan 31, 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
- GPT-4o$45.00
- Mixtral 8x22B Instruct$32.00
Which should you choose?
Which is better: Gemma 2 27B, GPT-4o or Mixtral 8x22B Instruct?
GPT-4o is the better all-round choice, scoring 43/100 against Gemma 2 27B (35) and Mixtral 8x22B Instruct (34). It leads on capability, inputs & features and context window. Gemma 2 27B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Gemma 2 27B, GPT-4o or Mixtral 8x22B Instruct?
Gemma 2 27B is cheaper at $0.65 input / $0.65 output per million tokens (median across 3 API providers). Mixtral 8x22B Instruct costs $2.00 input / $6.00 output per million tokens (median across 5 API providers); GPT-4o costs $2.50 input / $10.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $0.65 per million tokens for Gemma 2 27B versus $3.00 for Mixtral 8x22B Instruct (4.6× as much) and $4.38 for GPT-4o (6.7× as much).
Which scores higher on benchmarks?
GPT-4o scores higher on the Capabilities Index (ECI): GPT-4o 129.0 (#141 of 165), Gemma 2 27B 122.1 (#152 of 165) and Mixtral 8x22B Instruct 122.0 (#155 of 165). Their confidence ranges do not overlap (124.7–131.3 vs 115.8–124.1), so the gap is a real one. On individual benchmarks: GPQA Diamond — GPT-4o 48.9%, Gemma 2 27B 36.5%, Mixtral 8x22B Instruct 34.1%.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 2 27B, GPT-4o and Mixtral 8x22B Instruct yet, so there is no like-for-like coding score. On overall capability, GPT-4o 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?
GPT-4o has the largest context window at 128,000 tokens, against 65,536 for Mixtral 8x22B Instruct and 8,192 for Gemma 2 27B. Maximum output per response: Gemma 2 27B up to 2,048, GPT-4o up to 16,384, Mixtral 8x22B Instruct up to 52,428 tokens.
Which can read images, PDFs, audio or video?
Gemma 2 27B accepts text; GPT-4o accepts text, images and PDFs; Mixtral 8x22B Instruct accepts text and PDFs. GPT-4o handles the widest range of inputs.
Are any of these open source?
Gemma 2 27B and Mixtral 8x22B Instruct publishes its weights and can be self-hosted; GPT-4o is proprietary.
Which is newer?
Gemma 2 27B is the newest, released Jul 13, 2024. GPT-4o came out May 13, 2024; Mixtral 8x22B Instruct came out Apr 17, 2024. Knowledge cutoff: Gemma 2 27B Jun 30, 2024, GPT-4o Sep 2023, Mixtral 8x22B Instruct Jan 31, 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.
