Claude Haiku 3 vs Llama-3.1-8B-Instruct vs Ministral 3B
Too close to call on our weighted score (Ministral 3B 49, Claude Haiku 3 47, Llama-3.1-8B-Instruct 46). The right pick depends on what you value most.
AnthropicClaude Haiku 3
47/100- ECI118.4
- Price$0.25 / $1.25
- Context200K
MetaLlama-3.1-8B-Instruct
46/100- ECI116.6
- Price$0.152 / $0.167
- Context128K
Mistral AIMinistral 3B
49/100- ECI118.1
- Price$0.10 / $0.10
- Context128K
Too close to call
It is close. Our weighted score puts them within 2 points (Ministral 3B 49/100, Claude Haiku 3 47/100, Llama-3.1-8B-Instruct 46/100), so choose by what matters most for your work: Claude Haiku 3 for raw capability and Ministral 3B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityClaude Haiku 3Capabilities Index (ECI): Claude Haiku 3 118.4 · Ministral 3B 118.1 · Llama-3.1-8B-Instruct 116.6
- Lowest priceMinistral 3BMinistral 3B $0.10 · Llama-3.1-8B-Instruct $0.156 · Claude Haiku 3 $0.50 per 1M tokens (3:1 blend)
- Longest contextClaude Haiku 3Claude Haiku 3 200,000 · Llama-3.1-8B-Instruct 128,000 · Ministral 3B 128,000 tokens
- Widest inputsClaude Haiku 3Claude Haiku 3: Text, Images, PDFs · Llama-3.1-8B-Instruct: Text · Ministral 3B: Text
- Self-hostingLlama-3.1-8B-Instruct and Ministral 3BPublishes downloadable weights
| Measure | Weight | Claude Haiku 3 | Llama-3.1-8B-Instruct | Ministral 3B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 38 | 36 | 38 |
| Price | 25% | 64 | 88 | 97 |
| Inputs & features | 15% | 60 | 25 | 25 |
| Context window | 10% | 32 | 24 | 24 |
| Overall | 100% | 47/100 | 46/100 | 49/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Claude Haiku 3Anthropic | Llama-3.1-8B-InstructMeta | Ministral 3BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 118.4 (best) | 116.6 | 118.1 |
| ECI rank | #143 of 148 (best) | #145 of 148 | #144 of 148 |
| GPQA DiamondGraduate-level science questions | 36.3% (best) | 27.0% | 25.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | 1.8% (best) | 1.7% | — |
| Price per million tokens | |||
| Input | $0.25 | $0.152 | $0.10 (best) |
| Output | $1.25 | $0.167 | $0.10 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.50 | $0.156 | $0.10 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 2 providers | Median of 9 providers | Median of 1 providers |
| Limits | |||
| Context window | 200,000 tokens (best) | 128,000 tokens | 128,000 tokens |
| Max output | 4,096 tokens | 4,096 tokens | 8,192 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | Yes | No | 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 | Proprietary | Open | Open |
| API model ID | — | — | — |
| API providers | 2 | 9 (best) | 1 |
| Released | Mar 13, 2024 | Jul 23, 2024 | Oct 16, 2024 |
| Knowledge cutoff | Aug 31, 2023 | Dec 2023 | Mar 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Claude Haiku 3$5.00
- Llama-3.1-8B-Instruct$1.85
- Ministral 3B$1.20
Which should you choose?
Which is better: Claude Haiku 3, Llama-3.1-8B-Instruct or Ministral 3B?
It is close. Our weighted score puts them within 2 points (Ministral 3B 49/100, Claude Haiku 3 47/100, Llama-3.1-8B-Instruct 46/100), so choose by what matters most for your work: Claude Haiku 3 for raw capability and Ministral 3B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Claude Haiku 3, Llama-3.1-8B-Instruct or Ministral 3B?
Ministral 3B is cheaper at $0.10 input / $0.10 output per million tokens (median across 1 API provider). Llama-3.1-8B-Instruct costs $0.152 input / $0.167 output per million tokens (median across 9 API providers); Claude Haiku 3 costs $0.25 input / $1.25 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.10 per million tokens for Ministral 3B versus $0.156 for Llama-3.1-8B-Instruct (1.6× as much) and $0.50 for Claude Haiku 3 (5× as much).
Which scores higher on benchmarks?
Claude Haiku 3 scores higher on the Capabilities Index (ECI): Claude Haiku 3 118.4 (#143 of 148), Ministral 3B 118.1 (#144 of 148) and Llama-3.1-8B-Instruct 116.6 (#145 of 148). The confidence ranges of the top two overlap (110.5–121.2 vs 107.4–121.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Claude Haiku 3 36.3%, Llama-3.1-8B-Instruct 27.0%, Ministral 3B 25.3%.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Haiku 3, Llama-3.1-8B-Instruct and Ministral 3B yet, so there is no like-for-like coding score. On overall capability, Claude Haiku 3 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 has the largest context window at 200,000 tokens, against 128,000 for Llama-3.1-8B-Instruct and 128,000 for Ministral 3B. Maximum output per response: Claude Haiku 3 up to 4,096, Llama-3.1-8B-Instruct up to 4,096, Ministral 3B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Claude Haiku 3 accepts text, images and PDFs; Llama-3.1-8B-Instruct accepts text; Ministral 3B accepts text. Claude Haiku 3 handles the widest range of inputs.
Are any of these open source?
Llama-3.1-8B-Instruct and Ministral 3B publishes its weights and can be self-hosted; Claude Haiku 3 is proprietary.
Which is newer?
Ministral 3B is the newest, released Oct 16, 2024. Llama-3.1-8B-Instruct came out Jul 23, 2024; Claude Haiku 3 came out Mar 13, 2024. Knowledge cutoff: Claude Haiku 3 Aug 31, 2023, Llama-3.1-8B-Instruct Dec 2023, Ministral 3B Mar 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 Oct 4, 2026.
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