Gemma 3 12B IT vs Claude Haiku 3.5 vs Llama-3.3-70B-Instruct
Claude Haiku 3.5 comes out ahead, 49 to 43 and 41 on our weighted score.
Google
Gemma 3 12B IT
43/100- ECI123.5
- Price$0.05 / $0.15
- Context131K
- Our pick
Anthropic
Claude Haiku 3.5
49/100- ECI127.2
- Price—
- Context200K
Meta
Llama-3.3-70B-Instruct
41/100- ECI127.3
- Price$0.59 / $0.724
- Context128K
Claude Haiku 3.5 is our pick
Claude Haiku 3.5 is the better all-round choice, scoring 49/100 against Gemma 3 12B IT (43) and Llama-3.3-70B-Instruct (41). It leads on inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityLlama-3.3-70B-InstructCapabilities Index (ECI): Llama-3.3-70B-Instruct 127.3 · Claude Haiku 3.5 127.2 · Gemma 3 12B IT 123.5
- Lowest priceGemma 3 12B ITGemma 3 12B IT $0.075 · Llama-3.3-70B-Instruct $0.624 per 1M tokens (3:1 blend) · Claude Haiku 3.5 unpriced
- Longest contextClaude Haiku 3.5Claude Haiku 3.5 200,000 · Gemma 3 12B IT 131,072 · Llama-3.3-70B-Instruct 128,000 tokens
- Widest inputsClaude Haiku 3.5Gemma 3 12B IT: Text, Images · Claude Haiku 3.5: Text, Images, PDFs · Llama-3.3-70B-Instruct: Text
- Self-hostingGemma 3 12B IT and Llama-3.3-70B-InstructPublishes downloadable weights
| Measure | Weight | Gemma 3 12B IT | Claude Haiku 3.5 | Llama-3.3-70B-Instruct |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 45 | 49 | 49 |
| Inputs & features | 20% | 50 | 60 | 25 |
| Context window | 13% | 24 | 32 | 24 |
| Overall | 100% | 43/100 | 49/100 | 41/100 |
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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 123.5 | 127.2 | 127.3 (best) |
| ECI rank | #138 of 148 | #134 of 148 | #133 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 39.5% | 38.1% | 47.4% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 16.7% (best) | 4.3% | 5.1% |
| Price per million tokens | |||
| Input | $0.05 (best) | — | $0.59 |
| Output | $0.15 (best) | — | $0.724 |
| Cached input | — | — | — |
| Blended (3:1) | $0.075 (best) | — | $0.624 |
| Long-context rate | Same rate | — | Same rate |
| Price source | Median of 7 providers | — | Median of 21 providers |
| Limits | |||
| Context window | 131,072 tokens | 200,000 tokens (best) | 128,000 tokens |
| Max output | 131,072 tokens (best) | 8,192 tokens | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Proprietary | Open |
| API model ID | — | — | llama-3.3-70b-instruct |
| API providers | 7 | — | 24 (best) |
| Released | Mar 12, 2025 | Oct 22, 2024 | Dec 6, 2024 |
| Knowledge cutoff | Aug 2024 | Jul 31, 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 3 12B IT$0.80
Claude Haiku 3.5—
Llama-3.3-70B-Instruct$7.35
Which should you choose?
Which is better: Gemma 3 12B IT, Claude Haiku 3.5 or Llama-3.3-70B-Instruct?
Claude Haiku 3.5 is the better all-round choice, scoring 49/100 against Gemma 3 12B IT (43) and Llama-3.3-70B-Instruct (41). It leads on inputs & features and context window. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Gemma 3 12B IT, Claude Haiku 3.5 or Llama-3.3-70B-Instruct?
Gemma 3 12B IT is cheaper at $0.05 input / $0.15 output per million tokens (median across 7 API providers). Llama-3.3-70B-Instruct costs $0.59 input / $0.724 output per million tokens (median across 21 API providers; free on Llama). At a typical mix of three input tokens to one output token, that is $0.075 per million tokens for Gemma 3 12B IT versus $0.624 for Llama-3.3-70B-Instruct (8.3× as much). Claude Haiku 3.5 has no published per-token price.
Which scores higher on benchmarks?
Llama-3.3-70B-Instruct scores higher on the Capabilities Index (ECI): Llama-3.3-70B-Instruct 127.3 (#133 of 148), Claude Haiku 3.5 127.2 (#134 of 148) and Gemma 3 12B IT 123.5 (#138 of 148). The confidence ranges of the top two overlap (122.5–129.5 vs 120.7–129.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama-3.3-70B-Instruct 47.4%, Gemma 3 12B IT 39.5%, Claude Haiku 3.5 38.1%; OTIS Mock AIME 2024–2025 — Gemma 3 12B IT 16.7%, Llama-3.3-70B-Instruct 5.1%, Claude Haiku 3.5 4.3%.
Which is better for coding?
There are no published SWE-bench Verified results for Gemma 3 12B IT, Claude Haiku 3.5 and Llama-3.3-70B-Instruct yet, so there is no like-for-like coding score. On overall capability, Llama-3.3-70B-Instruct 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?
Claude Haiku 3.5 has the largest context window at 200,000 tokens, against 131,072 for Gemma 3 12B IT and 128,000 for Llama-3.3-70B-Instruct. Maximum output per response: Gemma 3 12B IT up to 131,072, Claude Haiku 3.5 up to 8,192, Llama-3.3-70B-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Gemma 3 12B IT accepts text and images; Claude Haiku 3.5 accepts text, images and PDFs; Llama-3.3-70B-Instruct accepts text. Claude Haiku 3.5 handles the widest range of inputs.
Are any of these open source?
Gemma 3 12B IT and Llama-3.3-70B-Instruct publishes its weights and can be self-hosted; Claude Haiku 3.5 is proprietary.
Which is newer?
Gemma 3 12B IT is the newest, released Mar 12, 2025. Llama-3.3-70B-Instruct came out Dec 6, 2024; Claude Haiku 3.5 came out Oct 22, 2024. Knowledge cutoff: Gemma 3 12B IT Aug 2024, Claude Haiku 3.5 Jul 31, 2024, Llama-3.3-70B-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 Oct 4, 2026.