ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Qwen2.5 7B Instruct vs Mistral Nemo vs Claude Haiku 3

Too close to call on our weighted score (Mistral Nemo 48, Claude Haiku 3 47, Qwen2.5 7B Instruct 44). The right pick depends on what you value most.

  1. Alibaba (Qwen)

    Qwen2.5 7B Instruct

    Released Sep 19, 2024

    44/100
    • ECI118.5
    • Price$0.175 / $0.70
    • Context131K
    Full specs Remove Qwen2.5 7B Instruct

  2. Mistral AI

    Mistral Nemo

    Released Jul 1, 2024

    48/100
    • ECI118.7
    • Price$0.15 / $0.15
    • Context128K
    Full specs Remove Mistral Nemo

  3. Anthropic

    Claude Haiku 3

    Released Mar 13, 2024

    47/100
    • ECI118.4
    • Price$0.25 / $1.25
    • Context200K
    Full specs Remove Claude Haiku 3
01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (Mistral Nemo 48/100, Claude Haiku 3 47/100, Qwen2.5 7B Instruct 44/100), so choose by what matters most for your work: Mistral Nemo for raw capability and Claude Haiku 3 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityMistral NemoCapabilities Index (ECI): Mistral Nemo 118.7 · Qwen2.5 7B Instruct 118.5 · Claude Haiku 3 118.4
  • Lowest priceMistral NemoMistral Nemo $0.15 · Qwen2.5 7B Instruct $0.306 · Claude Haiku 3 $0.50 per 1M tokens (3:1 blend)
  • Longest contextClaude Haiku 3Claude Haiku 3 200,000 · Qwen2.5 7B Instruct 131,072 · Mistral Nemo 128,000 tokens
  • Widest inputsClaude Haiku 3Qwen2.5 7B Instruct: Text · Mistral Nemo: Text · Claude Haiku 3: Text, Images, PDFs
  • Self-hostingQwen2.5 7B Instruct and Mistral NemoPublishes downloadable weights
How the score is built
MeasureWeightQwen2.5 7B InstructMistral NemoClaude Haiku 3
CapabilityCapabilities Index (ECI)50%383938
Price25%748964
Inputs & features15%252560
Context window10%242432
Overall100%44/10048/10047/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Qwen2.5 7B Instruct vs Mistral Nemo vs Claude Haiku 3 specifications side by side
SpecificationQwen2.5 7B InstructAlibaba (Qwen)Mistral NemoMistral AIClaude Haiku 3Anthropic
Capability
Capabilities Index (ECI)118.5118.7 (best)118.4
ECI rank#141 of 148#140 of 148 (best)#143 of 148
GPQA DiamondGraduate-level science questions35.5%29.9%36.3% (best)
OTIS Mock AIME 2024–2025Competition mathematics2.5% (best)—1.8%
Price per million tokens
Input$0.175$0.15 (best)$0.25
Output$0.70$0.15 (best)$1.25
Cached input———
Blended (3:1)$0.306$0.15 (best)$0.50
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Alibaba APIOfficial Mistral APIMedian of 2 providers
Limits
Context window131,072 tokens128,000 tokens200,000 tokens (best)
Max output8,192 tokens128,000 tokens (best)4,096 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoYes
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenProprietary
API model IDqwen2-5-7b-instructmistral-nemo—
API providers15 (best)2
ReleasedSep 19, 2024Jul 1, 2024Mar 13, 2024
Knowledge cutoffApr 2024Jul 2024Aug 31, 2023
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • Qwen2.5 7B Instruct$3.15
  • Mistral Nemo$1.80
  • Claude Haiku 3$5.00
04 — Questions

Which should you choose?

Which is better: Qwen2.5 7B Instruct, Mistral Nemo or Claude Haiku 3?

It is close. Our weighted score puts them within a point (Mistral Nemo 48/100, Claude Haiku 3 47/100, Qwen2.5 7B Instruct 44/100), so choose by what matters most for your work: Mistral Nemo for raw capability and Claude Haiku 3 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen2.5 7B Instruct, Mistral Nemo or Claude Haiku 3?

Mistral Nemo is cheaper at $0.15 input / $0.15 output per million tokens (official Mistral API price). Qwen2.5 7B Instruct costs $0.175 input / $0.70 output per million tokens (official Alibaba API price); 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 $0.15 per million tokens for Mistral Nemo versus $0.306 for Qwen2.5 7B Instruct (2× as much) and $0.50 for Claude Haiku 3 (3.3× as much).

Which scores higher on benchmarks?

Mistral Nemo scores higher on the Capabilities Index (ECI): Mistral Nemo 118.7 (#140 of 148), Qwen2.5 7B Instruct 118.5 (#141 of 148) and Claude Haiku 3 118.4 (#143 of 148). The confidence ranges of the top two overlap (111.3–121.5 vs 110.7–121.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — Claude Haiku 3 36.3%, Qwen2.5 7B Instruct 35.5%, Mistral Nemo 29.9%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen2.5 7B Instruct, Mistral Nemo and Claude Haiku 3 yet, so there is no like-for-like coding score. On overall capability, Mistral Nemo 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 131,072 for Qwen2.5 7B Instruct and 128,000 for Mistral Nemo. Maximum output per response: Qwen2.5 7B Instruct up to 8,192, Mistral Nemo up to 128,000, Claude Haiku 3 up to 4,096 tokens.

Which can read images, PDFs, audio or video?

Qwen2.5 7B Instruct accepts text; Mistral Nemo accepts text; Claude Haiku 3 accepts text, images and PDFs. Claude Haiku 3 handles the widest range of inputs.

Are any of these open source?

Qwen2.5 7B Instruct and Mistral Nemo publishes its weights and can be self-hosted; Claude Haiku 3 is proprietary.

Which is newer?

Qwen2.5 7B Instruct is the newest, released Sep 19, 2024. Mistral Nemo came out Jul 1, 2024; Claude Haiku 3 came out Mar 13, 2024. Knowledge cutoff: Qwen2.5 7B Instruct Apr 2024, Mistral Nemo Jul 2024, Claude Haiku 3 Aug 31, 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.

05 — Keep comparing

Related comparisons