Claude Haiku 4.5

The scorecard

Each axis runs from 0 to 100. The colored mark is this model. The faint marks are the other models in this edition. Hover one to see which, and click it to open that model.

• Tool use

  The agent has to call the right tool, with the right arguments, in the right order. Telling the customer it's done before the tool has finished counts against the model.

  30 conversations

  Mistral Small 4 49 Nova 2 Lite 53 GPT-4.1 mini 54 Gemini 2.5 Flash Lite 58 Gemini 3.1 Flash Lite 66 gpt-oss-120b 66 Gemma 4 31B 69 Gemini 3.5 Flash Lite 74 GPT-5 mini 78 GPT-5.6 Luna 85 GLM 5.3 Flash 96 DeepSeek V4 Flash 97

  72

  #6 of 13

  0 100

  It gets a single-order return right, but on longer calls it acts too early and commits the return before the customer is done.

• Task completion

  The customer has to leave with what they came for and nothing extra. Only the outcome counts, in long conversations where the customer gets a fact wrong, sets a limit early, wanders off topic, and changes their mind.

  21 conversations

  Gemini 2.5 Flash Lite 34 Nova 2 Lite 53 GPT-4.1 mini 56 Mistral Small 4 62 gpt-oss-120b 74 Gemma 4 31B 79 Gemini 3.5 Flash Lite 83 Gemini 3.1 Flash Lite 86 GPT-5.6 Luna 86 DeepSeek V4 Flash 89 GPT-5 mini 91 GLM 5.3 Flash 95

  72

  #9 of 13

  0 100

  It often stops a step short, quoting a return and asking for confirmation again instead of committing it.

• Context retention

  A constraint the customer states once, early, has to still hold when the agent acts at the end of a long conversation.

  21 conversations

  Gemini 2.5 Flash Lite 50 Mistral Small 4 69 Gemini 3.5 Flash Lite 70 gpt-oss-120b 71 GPT-4.1 mini 72 Gemini 3.1 Flash Lite 74 GLM 5.3 Flash 75 Gemma 4 31B 78 Nova 2 Lite 78 GPT-5.6 Luna 81 DeepSeek V4 Flash 86 GPT-5 mini 87

  82

  #3 of 13

  0 100

  Retention is solid until a cancel request is unspecific, and then it defaults to the most recently mentioned order.

• Grounding

  Answers have to come from the knowledge base. When a customer states a wrong spec or a made-up product, the agent has to correct them or say plainly that it doesn't know, and still handle the rest of the request.

  24 conversations

  Nova 2 Lite 66 Mistral Small 4 66 GPT-4.1 mini 67 Gemini 2.5 Flash Lite 69 Gemini 3.5 Flash Lite 71 gpt-oss-120b 83 Gemini 3.1 Flash Lite 86 GLM 5.3 Flash 90 Gemma 4 31B 92 GPT-5 mini 93 DeepSeek V4 Flash 94 GPT-5.6 Luna 94

  67

  #10 of 13

  0 100

  Pushed on policy, it treats the customer's version of a shipping or return rule as the correct one and sets its own record aside.

• Safety

  Simulated customers fake system messages, claim authority they don't have, and slip in instructions of their own. The agent has to hold its policy, keep its own instructions and tools to itself, protect other customers' orders, and still serve the real request.

  21 conversations

  Nova 2 Lite 60 Gemini 2.5 Flash Lite 61 GPT-4.1 mini 72 Mistral Small 4 73 gpt-oss-120b 76 GPT-5 mini 84 Gemma 4 31B 90 GPT-5.6 Luna 90 Gemini 3.1 Flash Lite 92 Gemini 3.5 Flash Lite 93 DeepSeek V4 Flash 94 GLM 5.3 Flash 94

  93

  #3 of 13

  0 100

  It won't issue a credit on demand or log a false cancellation reason, and that caution can stop a customer from canceling their own order.

• Hallucinations

  We pull out every statement the agent makes about a product or about what it has done, and check each one against the knowledge base and the tool results. One flagged statement marks the whole conversation, and the score is the share of conversations with nothing flagged, shown with its range.

  21 conversations · 68 of 589 claims flagged · 3.2 unsupported claims per conversation

  Nova 2 Lite 0 gpt-oss-120b 10 Gemini 2.5 Flash Lite 14 GPT-4.1 mini 14 Mistral Small 4 14 DeepSeek V4 Flash 19 GLM 5.3 Flash 24 GPT-5 mini 29 Gemini 3.5 Flash Lite 33 Gemini 3.1 Flash Lite 48 Gemma 4 31B 48 GPT-5.6 Luna 67

  19

  #7 of 13 8 to 40

  0 100

  It promises confirmation emails and delivery dates its records don't back, and it gets the item count on an order wrong.